id	sid	tid	token	lemma	pos
flr-135	1	1	frontline	frontline	NOUN
flr-135	1	2	learning	learn	VERB
flr-135	1	3	research	research	NOUN
flr-135	1	4	6	6	NUM
flr-135	1	5	(	(	PUNCT
flr-135	1	6	2014	2014	NUM
flr-135	1	7	)	)	PUNCT
flr-135	1	8	67	67	NUM
flr-135	1	9	-	-	SYM
flr-135	1	10	81	81	NUM
flr-135	1	11	issn	issn	PROPN
flr-135	1	12	2295	2295	NUM
flr-135	1	13	-	-	SYM
flr-135	1	14	3159	3159	NUM
flr-135	1	15	corresponding	corresponding	ADJ
flr-135	1	16	authors	author	NOUN
flr-135	1	17	:	:	PUNCT
flr-135	1	18	eduardo	eduardo	PROPN
flr-135	1	19	cascallar	cascallar	PROPN
flr-135	1	20	,	,	PUNCT
flr-135	1	21	ku	ku	PROPN
flr-135	1	22	leuven	leuven	PROPN
flr-135	1	23	,	,	PUNCT
flr-135	1	24	leuven	leuven	PROPN
flr-135	1	25	,	,	PUNCT
flr-135	1	26	belgium	belgium	PROPN
flr-135	1	27	,	,	PUNCT
flr-135	1	28	cascallar@msn.com	cascallar@msn.com	PROPN
flr-135	1	29	and	and	CCONJ
flr-135	1	30	mariel	mariel	PROPN
flr-135	1	31	musso	musso	PROPN
flr-135	1	32	,	,	PUNCT
flr-135	1	33	national	national	PROPN
flr-135	1	34	research	research	PROPN
flr-135	1	35	council	council	PROPN
flr-135	1	36	(	(	PUNCT
flr-135	1	37	conicet	conicet	PROPN
flr-135	1	38	)	)	PUNCT
flr-135	1	39	,	,	PUNCT
flr-135	1	40	argentina	argentina	PROPN
flr-135	1	41	and	and	CCONJ
flr-135	1	42	ku	ku	PROPN
flr-135	1	43	leuven	leuven	PROPN
flr-135	1	44	,	,	PUNCT
flr-135	1	45	leuven	leuven	PROPN
flr-135	1	46	,	,	PUNCT
flr-135	1	47	belgium	belgium	PROPN
flr-135	1	48	,	,	PUNCT
flr-135	1	49	mariel.musso@hotmail.com	mariel.musso@hotmail.com	X
flr-135	1	50	doi	doi	PROPN
flr-135	1	51	:	:	PUNCT
flr-135	1	52	http://dx.doi.org/10.14786/flr.v2i5.135	http://dx.doi.org/10.14786/flr.v2i5.135	NUM
flr-135	1	53	67	67	NUM
flr-135	2	1	|	|	CCONJ
flr-135	2	2	f	f	NOUN
flr-135	2	3	l	l	NOUN
flr-135	2	4	r	r	NOUN
flr-135	2	5	modelling	modelling	NOUN
flr-135	2	6	for	for	ADP
flr-135	2	7	understanding	understanding	NOUN
flr-135	2	8	and	and	CCONJ
flr-135	2	9	for	for	ADP
flr-135	2	10	prediction	prediction	NOUN
flr-135	2	11	/	/	SYM
flr-135	2	12	classification	classification	NOUN
flr-135	2	13	the	the	DET
flr-135	2	14	power	power	NOUN
flr-135	2	15	of	of	ADP
flr-135	2	16	neural	neural	ADJ
flr-135	2	17	networks	network	NOUN
flr-135	2	18	in	in	ADP
flr-135	2	19	research	research	NOUN
flr-135	2	20	eduardo	eduardo	PROPN
flr-135	2	21	cascallar	cascallar	PROPN
flr-135	2	22	ab	ab	PROPN
flr-135	2	23	,	,	PUNCT
flr-135	2	24	mariel	mariel	PROPN
flr-135	2	25	musso	musso	PROPN
flr-135	2	26	acd	acd	PROPN
flr-135	2	27	,	,	PUNCT
flr-135	2	28	eva	eva	PROPN
flr-135	2	29	kyndt	kyndt	PROPN
flr-135	2	30	a	a	PROPN
flr-135	2	31	and	and	CCONJ
flr-135	2	32	filip	filip	NOUN
flr-135	2	33	dochy	dochy	NOUN
flr-135	2	34	a	a	DET
flr-135	2	35	a	a	DET
flr-135	2	36	university	university	NOUN
flr-135	2	37	of	of	ADP
flr-135	2	38	leuven	leuven	PROPN
flr-135	2	39	,	,	PUNCT
flr-135	2	40	belgium	belgium	PROPN
flr-135	2	41	b	b	PROPN
flr-135	2	42	assessment	assessment	NOUN
flr-135	2	43	group	group	PROPN
flr-135	2	44	international	international	PROPN
flr-135	2	45	,	,	PUNCT
flr-135	2	46	usa	usa	PROPN
flr-135	2	47	/	/	SYM
flr-135	2	48	belgium	belgium	PROPN
flr-135	2	49	c	c	PROPN
flr-135	2	50	national	national	PROPN
flr-135	2	51	research	research	PROPN
flr-135	2	52	council	council	PROPN
flr-135	2	53	(	(	PUNCT
flr-135	2	54	conicet)/ciipme	conicet)/ciipme	PROPN
flr-135	2	55	,	,	PUNCT
flr-135	2	56	argentina	argentina	PROPN
flr-135	2	57	d	d	PROPN
flr-135	2	58	universidad	universidad	PROPN
flr-135	2	59	argentina	argentina	PROPN
flr-135	2	60	de	de	PROPN
flr-135	2	61	la	la	PROPN
flr-135	2	62	empresa	empresa	PROPN
flr-135	2	63	,	,	PUNCT
flr-135	2	64	argentina	argentina	PROPN
flr-135	2	65	article	article	PROPN
flr-135	2	66	received	receive	VERB
flr-135	2	67	28	28	NUM
flr-135	2	68	november	november	PROPN
flr-135	2	69	2014	2014	NUM
flr-135	2	70	/	/	SYM
flr-135	2	71	revised	revise	VERB
flr-135	2	72	18	18	NUM
flr-135	2	73	january	january	PROPN
flr-135	2	74	2015	2015	NUM
flr-135	2	75	/	/	PUNCT
flr-135	2	76	accepted	accept	VERB
flr-135	2	77	18	18	NUM
flr-135	2	78	january	january	PROPN
flr-135	2	79	2015	2015	NUM
flr-135	2	80	/	/	SYM
flr-135	2	81	available	available	ADJ
flr-135	2	82	online	online	ADJ
flr-135	2	83	30	30	NUM
flr-135	2	84	january	january	PROPN
flr-135	2	85	2015	2015	NUM
flr-135	2	86	abstract	abstract	ADJ
flr-135	2	87	two	two	NUM
flr-135	2	88	articles	article	NOUN
flr-135	2	89	,	,	PUNCT
flr-135	2	90	edelsbrunner	edelsbrunner	NOUN
flr-135	2	91	and	and	CCONJ
flr-135	2	92	,	,	PUNCT
flr-135	2	93	schneider	schneider	NOUN
flr-135	2	94	(	(	PUNCT
flr-135	2	95	2013	2013	NUM
flr-135	2	96	)	)	PUNCT
flr-135	2	97	,	,	PUNCT
flr-135	2	98	and	and	CCONJ
flr-135	2	99	nokelainen	nokelainen	NOUN
flr-135	2	100	and	and	CCONJ
flr-135	2	101	silander	silander	NOUN
flr-135	2	102	(	(	PUNCT
flr-135	2	103	2014	2014	NUM
flr-135	2	104	)	)	PUNCT
flr-135	2	105	comment	comment	NOUN
flr-135	2	106	on	on	ADP
flr-135	2	107	musso	musso	PROPN
flr-135	2	108	,	,	PUNCT
flr-135	2	109	kyndt	kyndt	NOUN
flr-135	2	110	,	,	PUNCT
flr-135	2	111	cascallar	cascallar	ADJ
flr-135	2	112	,	,	PUNCT
flr-135	2	113	and	and	CCONJ
flr-135	2	114	dochy	dochy	NOUN
flr-135	2	115	(	(	PUNCT
flr-135	2	116	2013	2013	NUM
flr-135	2	117	)	)	PUNCT
flr-135	2	118	.	.	PUNCT
flr-135	3	1	several	several	ADJ
flr-135	3	2	relevant	relevant	ADJ
flr-135	3	3	issues	issue	NOUN
flr-135	3	4	are	be	AUX
flr-135	3	5	raised	raise	VERB
flr-135	3	6	and	and	CCONJ
flr-135	3	7	some	some	DET
flr-135	3	8	important	important	ADJ
flr-135	3	9	clarifications	clarification	NOUN
flr-135	3	10	are	be	AUX
flr-135	3	11	made	make	VERB
flr-135	3	12	in	in	ADP
flr-135	3	13	response	response	NOUN
flr-135	3	14	to	to	ADP
flr-135	3	15	both	both	DET
flr-135	3	16	commentaries	commentary	NOUN
flr-135	3	17	.	.	PUNCT
flr-135	4	1	predictive	predictive	ADJ
flr-135	4	2	systems	system	NOUN
flr-135	4	3	based	base	VERB
flr-135	4	4	on	on	ADP
flr-135	4	5	artificial	artificial	ADJ
flr-135	4	6	neural	neural	ADJ
flr-135	4	7	networks	network	NOUN
flr-135	4	8	continue	continue	VERB
flr-135	4	9	to	to	PART
flr-135	4	10	be	be	AUX
flr-135	4	11	the	the	DET
flr-135	4	12	focus	focus	NOUN
flr-135	4	13	of	of	ADP
flr-135	4	14	current	current	ADJ
flr-135	4	15	research	research	NOUN
flr-135	4	16	and	and	CCONJ
flr-135	4	17	several	several	ADJ
flr-135	4	18	advances	advance	NOUN
flr-135	4	19	have	have	AUX
flr-135	4	20	improved	improve	VERB
flr-135	4	21	the	the	DET
flr-135	4	22	model	model	NOUN
flr-135	4	23	building	building	NOUN
flr-135	4	24	and	and	CCONJ
flr-135	4	25	the	the	DET
flr-135	4	26	interpretation	interpretation	NOUN
flr-135	4	27	of	of	ADP
flr-135	4	28	the	the	DET
flr-135	4	29	resulting	result	VERB
flr-135	4	30	neural	neural	ADJ
flr-135	4	31	network	network	NOUN
flr-135	4	32	models	model	NOUN
flr-135	4	33	.	.	PUNCT
flr-135	5	1	what	what	PRON
flr-135	5	2	is	be	AUX
flr-135	5	3	needed	need	VERB
flr-135	5	4	is	be	AUX
flr-135	5	5	the	the	DET
flr-135	5	6	courage	courage	NOUN
flr-135	5	7	and	and	CCONJ
flr-135	5	8	open	open	ADJ
flr-135	5	9	-	-	PUNCT
flr-135	5	10	mindedness	mindedness	NOUN
flr-135	5	11	to	to	PART
flr-135	5	12	actually	actually	ADV
flr-135	5	13	explore	explore	VERB
flr-135	5	14	new	new	ADJ
flr-135	5	15	paths	path	NOUN
flr-135	5	16	and	and	CCONJ
flr-135	5	17	rigorously	rigorously	ADV
flr-135	5	18	apply	apply	VERB
flr-135	5	19	new	new	ADJ
flr-135	5	20	methodologies	methodology	NOUN
flr-135	5	21	which	which	PRON
flr-135	5	22	can	can	AUX
flr-135	5	23	perhaps	perhaps	ADV
flr-135	5	24	,	,	PUNCT
flr-135	5	25	sometimes	sometimes	ADV
flr-135	5	26	unexpectedly	unexpectedly	ADV
flr-135	5	27	,	,	PUNCT
flr-135	5	28	provide	provide	VERB
flr-135	5	29	new	new	ADJ
flr-135	5	30	conceptualisations	conceptualisation	NOUN
flr-135	5	31	and	and	CCONJ
flr-135	5	32	tools	tool	NOUN
flr-135	5	33	for	for	ADP
flr-135	5	34	theoretical	theoretical	ADJ
flr-135	5	35	advancement	advancement	NOUN
flr-135	5	36	and	and	CCONJ
flr-135	5	37	practical	practical	ADJ
flr-135	5	38	applied	applied	ADJ
flr-135	5	39	research	research	NOUN
flr-135	5	40	.	.	PUNCT
flr-135	6	1	this	this	PRON
flr-135	6	2	is	be	AUX
flr-135	6	3	particularly	particularly	ADV
flr-135	6	4	true	true	ADJ
flr-135	6	5	in	in	ADP
flr-135	6	6	the	the	DET
flr-135	6	7	fields	field	NOUN
flr-135	6	8	of	of	ADP
flr-135	6	9	educational	educational	ADJ
flr-135	6	10	science	science	NOUN
flr-135	6	11	and	and	CCONJ
flr-135	6	12	social	social	ADJ
flr-135	6	13	sciences	science	NOUN
flr-135	6	14	,	,	PUNCT
flr-135	6	15	where	where	SCONJ
flr-135	6	16	the	the	DET
flr-135	6	17	complexity	complexity	NOUN
flr-135	6	18	of	of	ADP
flr-135	6	19	the	the	DET
flr-135	6	20	problems	problem	NOUN
flr-135	6	21	to	to	PART
flr-135	6	22	be	be	AUX
flr-135	6	23	solved	solve	VERB
flr-135	6	24	requires	require	VERB
flr-135	6	25	the	the	DET
flr-135	6	26	exploration	exploration	NOUN
flr-135	6	27	of	of	ADP
flr-135	6	28	proven	prove	VERB
flr-135	6	29	methods	method	NOUN
flr-135	6	30	and	and	CCONJ
flr-135	6	31	new	new	ADJ
flr-135	6	32	methods	method	NOUN
flr-135	6	33	,	,	PUNCT
flr-135	6	34	the	the	DET
flr-135	6	35	latter	latter	ADJ
flr-135	6	36	usually	usually	ADV
flr-135	6	37	not	not	PART
flr-135	6	38	among	among	ADP
flr-135	6	39	the	the	DET
flr-135	6	40	common	common	ADJ
flr-135	6	41	arsenal	arsenal	NOUN
flr-135	6	42	of	of	ADP
flr-135	6	43	tools	tool	NOUN
flr-135	6	44	of	of	ADP
flr-135	6	45	neither	neither	CCONJ
flr-135	6	46	practitioners	practitioner	NOUN
flr-135	6	47	nor	nor	CCONJ
flr-135	6	48	researchers	researcher	NOUN
flr-135	6	49	in	in	ADP
flr-135	6	50	these	these	DET
flr-135	6	51	fields	field	NOUN
flr-135	6	52	.	.	PUNCT
flr-135	7	1	this	this	DET
flr-135	7	2	response	response	NOUN
flr-135	7	3	will	will	AUX
flr-135	7	4	enrich	enrich	VERB
flr-135	7	5	the	the	DET
flr-135	7	6	understanding	understanding	NOUN
flr-135	7	7	of	of	ADP
flr-135	7	8	the	the	DET
flr-135	7	9	predictive	predictive	ADJ
flr-135	7	10	systems	system	NOUN
flr-135	7	11	methodology	methodology	NOUN
flr-135	7	12	proposed	propose	VERB
flr-135	7	13	by	by	ADP
flr-135	7	14	the	the	DET
flr-135	7	15	authors	author	NOUN
flr-135	7	16	and	and	CCONJ
flr-135	7	17	clarify	clarify	VERB
flr-135	7	18	the	the	DET
flr-135	7	19	application	application	NOUN
flr-135	7	20	of	of	ADP
flr-135	7	21	the	the	DET
flr-135	7	22	procedure	procedure	NOUN
flr-135	7	23	,	,	PUNCT
flr-135	7	24	as	as	ADV
flr-135	7	25	well	well	ADV
flr-135	7	26	as	as	ADP
flr-135	7	27	give	give	VERB
flr-135	7	28	a	a	DET
flr-135	7	29	perspective	perspective	NOUN
flr-135	7	30	on	on	ADP
flr-135	7	31	its	its	PRON
flr-135	7	32	place	place	NOUN
flr-135	7	33	among	among	ADP
flr-135	7	34	other	other	ADJ
flr-135	7	35	predictive	predictive	ADJ
flr-135	7	36	approaches	approach	NOUN
flr-135	7	37	.	.	PUNCT
flr-135	8	1	keywords	keyword	NOUN
flr-135	8	2	:	:	PUNCT
flr-135	8	3	artificial	artificial	ADJ
flr-135	8	4	neural	neural	ADJ
flr-135	8	5	networks	network	NOUN
flr-135	8	6	;	;	PUNCT
flr-135	8	7	response	response	NOUN
flr-135	8	8	to	to	ADP
flr-135	8	9	commentaries	commentary	NOUN
flr-135	8	10	;	;	PUNCT
flr-135	8	11	methodology	methodology	NOUN
flr-135	8	12	;	;	PUNCT
flr-135	8	13	data	datum	NOUN
flr-135	8	14	modelling	model	VERB
flr-135	8	15	cascallar	cascallar	PROPN
flr-135	8	16	et	et	NOUN
flr-135	8	17	al	al	PROPN
flr-135	8	18	68	68	NUM
flr-135	9	1	|	|	CCONJ
flr-135	9	2	f	f	NOUN
flr-135	9	3	l	l	NOUN
flr-135	9	4	r	r	NOUN
flr-135	9	5	research	research	NOUN
flr-135	9	6	is	be	AUX
flr-135	9	7	the	the	DET
flr-135	9	8	process	process	NOUN
flr-135	9	9	of	of	ADP
flr-135	9	10	going	go	VERB
flr-135	9	11	up	up	ADP
flr-135	9	12	alleys	alley	NOUN
flr-135	9	13	to	to	PART
flr-135	9	14	see	see	VERB
flr-135	9	15	if	if	SCONJ
flr-135	9	16	they	they	PRON
flr-135	9	17	are	be	AUX
flr-135	9	18	blind	blind	ADJ
flr-135	9	19	.	.	PUNCT
flr-135	10	1	marston	marston	PROPN
flr-135	10	2	bates	bates	PROPN
flr-135	10	3	two	two	NUM
flr-135	10	4	articles	article	NOUN
flr-135	10	5	,	,	PUNCT
flr-135	10	6	edelsbrunner	edelsbrunner	NOUN
flr-135	10	7	and	and	CCONJ
flr-135	10	8	,	,	PUNCT
flr-135	10	9	schneider	schneider	NOUN
flr-135	10	10	(	(	PUNCT
flr-135	10	11	2013	2013	NUM
flr-135	10	12	)	)	PUNCT
flr-135	10	13	,	,	PUNCT
flr-135	10	14	and	and	CCONJ
flr-135	10	15	nokelainen	nokelainen	NOUN
flr-135	10	16	and	and	CCONJ
flr-135	10	17	silander	silander	NOUN
flr-135	10	18	(	(	PUNCT
flr-135	10	19	2014	2014	NUM
flr-135	10	20	)	)	PUNCT
flr-135	10	21	comment	comment	NOUN
flr-135	10	22	on	on	ADP
flr-135	10	23	musso	musso	PROPN
flr-135	10	24	,	,	PUNCT
flr-135	10	25	kyndt	kyndt	NOUN
flr-135	10	26	,	,	PUNCT
flr-135	10	27	cascallar	cascallar	ADJ
flr-135	10	28	,	,	PUNCT
flr-135	10	29	and	and	CCONJ
flr-135	10	30	dochy	dochy	NOUN
flr-135	10	31	(	(	PUNCT
flr-135	10	32	2013	2013	NUM
flr-135	10	33	)	)	PUNCT
flr-135	10	34	.	.	PUNCT
flr-135	11	1	several	several	ADJ
flr-135	11	2	relevant	relevant	ADJ
flr-135	11	3	issues	issue	NOUN
flr-135	11	4	are	be	AUX
flr-135	11	5	raised	raise	VERB
flr-135	11	6	and	and	CCONJ
flr-135	11	7	some	some	DET
flr-135	11	8	important	important	ADJ
flr-135	11	9	clarifications	clarification	NOUN
flr-135	11	10	need	need	VERB
flr-135	11	11	to	to	PART
flr-135	11	12	be	be	AUX
flr-135	11	13	made	make	VERB
flr-135	11	14	in	in	ADP
flr-135	11	15	response	response	NOUN
flr-135	11	16	to	to	ADP
flr-135	11	17	both	both	DET
flr-135	11	18	commentaries	commentary	NOUN
flr-135	11	19	.	.	PUNCT
flr-135	12	1	this	this	DET
flr-135	12	2	response	response	NOUN
flr-135	12	3	will	will	AUX
flr-135	12	4	enrich	enrich	VERB
flr-135	12	5	the	the	DET
flr-135	12	6	understanding	understanding	NOUN
flr-135	12	7	of	of	ADP
flr-135	12	8	the	the	DET
flr-135	12	9	predictive	predictive	ADJ
flr-135	12	10	system	system	NOUN
flr-135	12	11	methodology	methodology	NOUN
flr-135	12	12	proposed	propose	VERB
flr-135	12	13	by	by	ADP
flr-135	12	14	the	the	DET
flr-135	12	15	authors	author	NOUN
flr-135	12	16	and	and	CCONJ
flr-135	12	17	clarify	clarify	VERB
flr-135	12	18	the	the	DET
flr-135	12	19	application	application	NOUN
flr-135	12	20	of	of	ADP
flr-135	12	21	the	the	DET
flr-135	12	22	procedure	procedure	NOUN
flr-135	12	23	,	,	PUNCT
flr-135	12	24	as	as	ADV
flr-135	12	25	well	well	ADV
flr-135	12	26	as	as	ADP
flr-135	12	27	give	give	VERB
flr-135	12	28	a	a	DET
flr-135	12	29	perspective	perspective	NOUN
flr-135	12	30	on	on	ADP
flr-135	12	31	its	its	PRON
flr-135	12	32	place	place	NOUN
flr-135	12	33	among	among	ADP
flr-135	12	34	other	other	ADJ
flr-135	12	35	predictive	predictive	ADJ
flr-135	12	36	approaches	approach	NOUN
flr-135	12	37	.	.	PUNCT
flr-135	13	1	edelsbrunner	edelsbrunner	NOUN
flr-135	13	2	and	and	CCONJ
flr-135	13	3	schneider	schneider	NOUN
flr-135	13	4	(	(	PUNCT
flr-135	13	5	2013	2013	NUM
flr-135	13	6	)	)	PUNCT
flr-135	13	7	in	in	ADP
flr-135	13	8	their	their	PRON
flr-135	13	9	commentary	commentary	NOUN
flr-135	13	10	on	on	ADP
flr-135	13	11	musso	musso	PROPN
flr-135	13	12	,	,	PUNCT
flr-135	13	13	kyndt	kyndt	NOUN
flr-135	13	14	,	,	PUNCT
flr-135	13	15	cascallar	cascallar	ADJ
flr-135	13	16	and	and	CCONJ
flr-135	13	17	dochy	dochy	ADJ
flr-135	13	18	(	(	PUNCT
flr-135	13	19	2013	2013	NUM
flr-135	13	20	)	)	PUNCT
flr-135	13	21	argue	argue	VERB
flr-135	13	22	that	that	SCONJ
flr-135	13	23	artificial	artificial	ADJ
flr-135	13	24	neural	neural	ADJ
flr-135	13	25	networks	network	NOUN
flr-135	13	26	(	(	PUNCT
flr-135	13	27	anns	anns	PROPN
flr-135	13	28	)	)	PUNCT
flr-135	13	29	should	should	AUX
flr-135	13	30	only	only	ADV
flr-135	13	31	be	be	AUX
flr-135	13	32	used	use	VERB
flr-135	13	33	as	as	ADP
flr-135	13	34	exploratory	exploratory	ADJ
flr-135	13	35	modelling	modelling	NOUN
flr-135	13	36	techniques	technique	NOUN
flr-135	13	37	,	,	PUNCT
flr-135	13	38	in	in	ADP
flr-135	13	39	spite	spite	NOUN
flr-135	13	40	of	of	ADP
flr-135	13	41	being	be	AUX
flr-135	13	42	powerful	powerful	ADJ
flr-135	13	43	statistical	statistical	ADJ
flr-135	13	44	modelling	modelling	NOUN
flr-135	13	45	tools	tool	NOUN
flr-135	13	46	with	with	ADP
flr-135	13	47	demonstrated	demonstrate	VERB
flr-135	13	48	ability	ability	NOUN
flr-135	13	49	to	to	PART
flr-135	13	50	improve	improve	VERB
flr-135	13	51	outcomes	outcome	NOUN
flr-135	13	52	of	of	ADP
flr-135	13	53	classifications	classification	NOUN
flr-135	13	54	and	and	CCONJ
flr-135	13	55	predictions	prediction	NOUN
flr-135	13	56	over	over	ADP
flr-135	13	57	traditional	traditional	ADJ
flr-135	13	58	statistical	statistical	ADJ
flr-135	13	59	methods	method	NOUN
flr-135	13	60	(	(	PUNCT
flr-135	13	61	marquez	marquez	PROPN
flr-135	13	62	,	,	PUNCT
flr-135	13	63	hill	hill	PROPN
flr-135	13	64	,	,	PUNCT
flr-135	13	65	worthley	worthley	NOUN
flr-135	13	66	,	,	PUNCT
flr-135	13	67	&	&	CCONJ
flr-135	13	68	remus	remus	PROPN
flr-135	13	69	,	,	PUNCT
flr-135	13	70	1991	1991	NUM
flr-135	13	71	)	)	PUNCT
flr-135	13	72	.	.	PUNCT
flr-135	14	1	garson	garson	PROPN
flr-135	14	2	(	(	PUNCT
flr-135	14	3	1998	1998	NUM
flr-135	14	4	,	,	PUNCT
flr-135	14	5	pp	pp	ADJ
flr-135	14	6	.	.	PUNCT
flr-135	15	1	11	11	NUM
flr-135	15	2	-	-	SYM
flr-135	15	3	14	14	NUM
flr-135	15	4	)	)	PUNCT
flr-135	15	5	cites	cite	VERB
flr-135	15	6	more	more	ADJ
flr-135	15	7	than	than	ADP
flr-135	15	8	thirty	thirty	NUM
flr-135	15	9	-	-	PUNCT
flr-135	15	10	five	five	NUM
flr-135	15	11	articles	article	NOUN
flr-135	15	12	which	which	PRON
flr-135	15	13	have	have	AUX
flr-135	15	14	shown	show	VERB
flr-135	15	15	the	the	DET
flr-135	15	16	ability	ability	NOUN
flr-135	15	17	of	of	ADP
flr-135	15	18	anns	anns	NOUN
flr-135	15	19	to	to	PART
flr-135	15	20	outperform	outperform	VERB
flr-135	15	21	traditional	traditional	ADJ
flr-135	15	22	techniques	technique	NOUN
flr-135	15	23	in	in	ADP
flr-135	15	24	specific	specific	ADJ
flr-135	15	25	circumstances	circumstance	NOUN
flr-135	15	26	.	.	PUNCT
flr-135	16	1	in	in	ADP
flr-135	16	2	addition	addition	NOUN
flr-135	16	3	,	,	PUNCT
flr-135	16	4	haykin	haykin	X
flr-135	16	5	(	(	PUNCT
flr-135	16	6	1994	1994	NUM
flr-135	16	7	,	,	PUNCT
flr-135	16	8	pp	pp	ADJ
flr-135	16	9	.	.	PUNCT
flr-135	16	10	4	4	NUM
flr-135	16	11	-	-	SYM
flr-135	16	12	5	5	NUM
flr-135	16	13	)	)	PUNCT
flr-135	16	14	summarizes	summarize	NOUN
flr-135	16	15	some	some	PRON
flr-135	16	16	of	of	ADP
flr-135	16	17	the	the	DET
flr-135	16	18	main	main	ADJ
flr-135	16	19	favourable	favourable	ADJ
flr-135	16	20	properties	property	NOUN
flr-135	16	21	of	of	ADP
flr-135	16	22	anns	ann	NOUN
flr-135	16	23	which	which	PRON
flr-135	16	24	explain	explain	VERB
flr-135	16	25	their	their	PRON
flr-135	16	26	advantages	advantage	NOUN
flr-135	16	27	over	over	ADP
flr-135	16	28	traditional	traditional	ADJ
flr-135	16	29	methods	method	NOUN
flr-135	16	30	.	.	PUNCT
flr-135	17	1	the	the	DET
flr-135	17	2	reasons	reason	NOUN
flr-135	17	3	edelsbrunner	edelsbrunner	NOUN
flr-135	17	4	and	and	CCONJ
flr-135	17	5	schneider	schneider	NOUN
flr-135	17	6	(	(	PUNCT
flr-135	17	7	2013	2013	NUM
flr-135	17	8	)	)	PUNCT
flr-135	17	9	argue	argue	VERB
flr-135	17	10	for	for	SCONJ
flr-135	17	11	their	their	PRON
flr-135	17	12	rather	rather	ADV
flr-135	17	13	strong	strong	ADJ
flr-135	17	14	position	position	NOUN
flr-135	17	15	are	be	AUX
flr-135	17	16	centred	centre	VERB
flr-135	17	17	on	on	ADP
flr-135	17	18	two	two	NUM
flr-135	17	19	main	main	ADJ
flr-135	17	20	arguments	argument	NOUN
flr-135	17	21	:	:	PUNCT
flr-135	17	22	(	(	PUNCT
flr-135	17	23	a	a	X
flr-135	17	24	)	)	PUNCT
flr-135	17	25	that	that	SCONJ
flr-135	17	26	the	the	DET
flr-135	17	27	output	output	NOUN
flr-135	17	28	from	from	ADP
flr-135	17	29	anns	anns	NOUN
flr-135	17	30	can	can	AUX
flr-135	17	31	not	not	PART
flr-135	17	32	be	be	AUX
flr-135	17	33	fully	fully	ADV
flr-135	17	34	translated	translate	VERB
flr-135	17	35	into	into	ADP
flr-135	17	36	a	a	DET
flr-135	17	37	meaningful	meaningful	ADJ
flr-135	17	38	set	set	NOUN
flr-135	17	39	of	of	ADP
flr-135	17	40	rules	rule	NOUN
flr-135	17	41	because	because	SCONJ
flr-135	17	42	of	of	ADP
flr-135	17	43	a	a	DET
flr-135	17	44	lack	lack	NOUN
flr-135	17	45	of	of	ADP
flr-135	17	46	accessibility	accessibility	NOUN
flr-135	17	47	to	to	ADP
flr-135	17	48	the	the	DET
flr-135	17	49	input	input	NOUN
flr-135	17	50	-	-	PUNCT
flr-135	17	51	output	output	NOUN
flr-135	17	52	relationships	relationship	NOUN
flr-135	17	53	,	,	PUNCT
flr-135	17	54	and	and	CCONJ
flr-135	17	55	(	(	PUNCT
flr-135	17	56	b	b	X
flr-135	17	57	)	)	PUNCT
flr-135	17	58	that	that	SCONJ
flr-135	17	59	there	there	PRON
flr-135	17	60	is	be	VERB
flr-135	17	61	a	a	DET
flr-135	17	62	lack	lack	NOUN
flr-135	17	63	of	of	ADP
flr-135	17	64	equivalent	equivalent	ADJ
flr-135	17	65	statistical	statistical	ADJ
flr-135	17	66	parameters	parameter	NOUN
flr-135	17	67	in	in	ADP
flr-135	17	68	anns	anns	NOUN
flr-135	17	69	when	when	SCONJ
flr-135	17	70	compared	compare	VERB
flr-135	17	71	to	to	ADP
flr-135	17	72	more	more	ADV
flr-135	17	73	traditional	traditional	ADJ
flr-135	17	74	statistical	statistical	ADJ
flr-135	17	75	techniques	technique	NOUN
flr-135	17	76	.	.	PUNCT
flr-135	18	1	these	these	PRON
flr-135	18	2	are	be	AUX
flr-135	18	3	the	the	DET
flr-135	18	4	two	two	NUM
flr-135	18	5	fundamental	fundamental	ADJ
flr-135	18	6	misconceptions	misconception	NOUN
flr-135	18	7	that	that	PRON
flr-135	18	8	will	will	AUX
flr-135	18	9	be	be	AUX
flr-135	18	10	addressed	address	VERB
flr-135	18	11	.	.	PUNCT
flr-135	19	1	one	one	NUM
flr-135	19	2	of	of	ADP
flr-135	19	3	the	the	DET
flr-135	19	4	essential	essential	ADJ
flr-135	19	5	requirements	requirement	NOUN
flr-135	19	6	for	for	ADP
flr-135	19	7	development	development	NOUN
flr-135	19	8	and	and	CCONJ
flr-135	19	9	advancement	advancement	NOUN
flr-135	19	10	in	in	ADP
flr-135	19	11	science	science	NOUN
flr-135	19	12	is	be	AUX
flr-135	19	13	the	the	DET
flr-135	19	14	willingness	willingness	NOUN
flr-135	19	15	and	and	CCONJ
flr-135	19	16	vision	vision	NOUN
flr-135	19	17	to	to	PART
flr-135	19	18	explore	explore	VERB
flr-135	19	19	new	new	ADJ
flr-135	19	20	conceptualizations	conceptualization	NOUN
flr-135	19	21	and	and	CCONJ
flr-135	19	22	methods	method	NOUN
flr-135	19	23	.	.	PUNCT
flr-135	20	1	in	in	ADP
flr-135	20	2	particular	particular	ADJ
flr-135	20	3	,	,	PUNCT
flr-135	20	4	as	as	SCONJ
flr-135	20	5	is	be	AUX
flr-135	20	6	the	the	DET
flr-135	20	7	case	case	NOUN
flr-135	20	8	in	in	ADP
flr-135	20	9	the	the	DET
flr-135	20	10	study	study	NOUN
flr-135	20	11	by	by	ADP
flr-135	20	12	musso	musso	PROPN
flr-135	20	13	et	et	PROPN
flr-135	20	14	al	al	PROPN
flr-135	20	15	.	.	PROPN
flr-135	21	1	(	(	PUNCT
flr-135	21	2	2013	2013	NUM
flr-135	21	3	)	)	PUNCT
flr-135	22	1	,	,	PUNCT
flr-135	22	2	the	the	DET
flr-135	22	3	ability	ability	NOUN
flr-135	22	4	to	to	PART
flr-135	22	5	bring	bring	VERB
flr-135	22	6	together	together	ADV
flr-135	22	7	data	datum	NOUN
flr-135	22	8	from	from	ADP
flr-135	22	9	interdisciplinary	interdisciplinary	ADJ
flr-135	22	10	domains	domain	NOUN
flr-135	22	11	(	(	PUNCT
flr-135	22	12	e.g.	e.g.	ADV
flr-135	22	13	,	,	PUNCT
flr-135	22	14	decuyper	decuyper	NOUN
flr-135	22	15	,	,	PUNCT
flr-135	22	16	dochy	dochy	NOUN
flr-135	22	17	,	,	PUNCT
flr-135	22	18	&	&	CCONJ
flr-135	22	19	van	van	PROPN
flr-135	22	20	den	den	PROPN
flr-135	22	21	bossche	bossche	PROPN
flr-135	22	22	,	,	PUNCT
flr-135	22	23	2010	2010	NUM
flr-135	22	24	)	)	PUNCT
flr-135	22	25	,	,	PUNCT
flr-135	22	26	and	and	CCONJ
flr-135	22	27	to	to	PART
flr-135	22	28	use	use	VERB
flr-135	22	29	new	new	ADJ
flr-135	22	30	methodologies	methodology	NOUN
flr-135	22	31	for	for	ADP
flr-135	22	32	analyses	analysis	NOUN
flr-135	22	33	that	that	PRON
flr-135	22	34	are	be	AUX
flr-135	22	35	commonly	commonly	ADV
flr-135	22	36	applied	apply	VERB
flr-135	22	37	in	in	ADP
flr-135	22	38	other	other	ADJ
flr-135	22	39	disciplines	discipline	NOUN
flr-135	22	40	such	such	ADJ
flr-135	22	41	as	as	ADP
flr-135	22	42	business	business	NOUN
flr-135	22	43	,	,	PUNCT
flr-135	22	44	finance	finance	NOUN
flr-135	22	45	,	,	PUNCT
flr-135	22	46	and	and	CCONJ
flr-135	22	47	the	the	DET
flr-135	22	48	social	social	ADJ
flr-135	22	49	sciences	sciences	PROPN
flr-135	22	50	(	(	PUNCT
flr-135	22	51	aldeek	aldeek	NOUN
flr-135	22	52	,	,	PUNCT
flr-135	22	53	2001	2001	NUM
flr-135	22	54	;	;	PUNCT
flr-135	22	55	detienne	detienne	ADJ
flr-135	22	56	,	,	PUNCT
flr-135	22	57	detienne	detienne	PROPN
flr-135	22	58	,	,	PUNCT
flr-135	22	59	&	&	CCONJ
flr-135	22	60	joshi	joshi	PROPN
flr-135	22	61	,	,	PUNCT
flr-135	22	62	2003	2003	NUM
flr-135	22	63	;	;	PUNCT
flr-135	22	64	laguna	laguna	PROPN
flr-135	22	65	&	&	CCONJ
flr-135	22	66	marti	marti	PROPN
flr-135	22	67	,	,	PUNCT
flr-135	22	68	2002	2002	NUM
flr-135	22	69	;	;	PUNCT
flr-135	22	70	neal	neal	PROPN
flr-135	22	71	&	&	CCONJ
flr-135	22	72	wurst	wurst	PROPN
flr-135	22	73	,	,	PUNCT
flr-135	22	74	2001	2001	NUM
flr-135	22	75	;	;	PUNCT
flr-135	22	76	nguyen	nguyen	PROPN
flr-135	22	77	&	&	CCONJ
flr-135	22	78	cripps	cripps	PROPN
flr-135	22	79	,	,	PUNCT
flr-135	22	80	2001	2001	NUM
flr-135	22	81	;	;	PUNCT
flr-135	22	82	white	white	PROPN
flr-135	22	83	&	&	CCONJ
flr-135	22	84	racine	racine	PROPN
flr-135	22	85	,	,	PUNCT
flr-135	22	86	2001	2001	NUM
flr-135	22	87	,	,	PUNCT
flr-135	22	88	and	and	CCONJ
flr-135	22	89	others	other	NOUN
flr-135	22	90	as	as	SCONJ
flr-135	22	91	stated	state	VERB
flr-135	22	92	in	in	ADP
flr-135	22	93	musso	musso	PROPN
flr-135	22	94	et	et	PROPN
flr-135	22	95	al	al	PROPN
flr-135	22	96	.	.	PROPN
flr-135	22	97	,	,	PUNCT
flr-135	22	98	2003	2003	NUM
flr-135	22	99	)	)	PUNCT
flr-135	22	100	.	.	PUNCT
flr-135	23	1	the	the	DET
flr-135	23	2	literature	literature	NOUN
flr-135	23	3	still	still	ADV
flr-135	23	4	shows	show	VERB
flr-135	23	5	relatively	relatively	ADV
flr-135	23	6	few	few	ADJ
flr-135	23	7	studies	study	NOUN
flr-135	23	8	applying	apply	VERB
flr-135	23	9	neural	neural	ADJ
flr-135	23	10	networks	network	NOUN
flr-135	23	11	in	in	ADP
flr-135	23	12	education	education	NOUN
flr-135	23	13	and	and	CCONJ
flr-135	23	14	in	in	ADP
flr-135	23	15	educational	educational	ADJ
flr-135	23	16	assessment	assessment	NOUN
flr-135	23	17	in	in	ADP
flr-135	23	18	particular	particular	ADJ
flr-135	23	19	(	(	PUNCT
flr-135	23	20	everson	everson	NOUN
flr-135	23	21	,	,	PUNCT
flr-135	23	22	chance	chance	NOUN
flr-135	23	23	,	,	PUNCT
flr-135	23	24	&	&	CCONJ
flr-135	23	25	lykins	lykin	NOUN
flr-135	23	26	,	,	PUNCT
flr-135	23	27	1994	1994	NUM
flr-135	23	28	;	;	PUNCT
flr-135	23	29	wilson	wilson	PROPN
flr-135	23	30	&	&	CCONJ
flr-135	23	31	hardgrave	hardgrave	PROPN
flr-135	23	32	,	,	PUNCT
flr-135	23	33	1995	1995	NUM
flr-135	23	34	)	)	PUNCT
flr-135	23	35	,	,	PUNCT
flr-135	23	36	although	although	SCONJ
flr-135	23	37	anns	ann	NOUN
flr-135	23	38	have	have	AUX
flr-135	23	39	been	be	AUX
flr-135	23	40	shown	show	VERB
flr-135	23	41	to	to	PART
flr-135	23	42	improve	improve	VERB
flr-135	23	43	the	the	DET
flr-135	23	44	validity	validity	NOUN
flr-135	23	45	and	and	CCONJ
flr-135	23	46	the	the	DET
flr-135	23	47	accuracy	accuracy	NOUN
flr-135	23	48	of	of	ADP
flr-135	23	49	the	the	DET
flr-135	23	50	predictions	prediction	NOUN
flr-135	23	51	and/or	and/or	CCONJ
flr-135	23	52	classifications	classification	NOUN
flr-135	23	53	,	,	PUNCT
flr-135	23	54	and	and	CCONJ
flr-135	23	55	also	also	ADV
flr-135	23	56	improve	improve	VERB
flr-135	23	57	the	the	DET
flr-135	23	58	predictive	predictive	ADJ
flr-135	23	59	validity	validity	NOUN
flr-135	23	60	of	of	ADP
flr-135	23	61	test	test	NOUN
flr-135	23	62	scores	score	NOUN
flr-135	23	63	(	(	PUNCT
flr-135	23	64	everson	everson	PROPN
flr-135	23	65	et	et	PROPN
flr-135	23	66	al	al	PROPN
flr-135	23	67	.	.	PROPN
flr-135	23	68	,	,	PUNCT
flr-135	23	69	1994	1994	NUM
flr-135	23	70	;	;	PUNCT
flr-135	23	71	perkins	perkins	PROPN
flr-135	23	72	,	,	PUNCT
flr-135	23	73	gupta	gupta	PROPN
flr-135	23	74	,	,	PUNCT
flr-135	23	75	&	&	CCONJ
flr-135	23	76	tamanna	tamanna	PROPN
flr-135	23	77	,	,	PUNCT
flr-135	23	78	1995	1995	NUM
flr-135	23	79	;	;	PUNCT
flr-135	23	80	weiss	weiss	PROPN
flr-135	23	81	&	&	CCONJ
flr-135	23	82	kulikowski	kulikowski	PROPN
flr-135	23	83	,	,	PUNCT
flr-135	23	84	1991	1991	NUM
flr-135	23	85	)	)	PUNCT
flr-135	23	86	.	.	PUNCT
flr-135	24	1	more	more	ADV
flr-135	24	2	recently	recently	ADV
flr-135	24	3	,	,	PUNCT
flr-135	24	4	several	several	ADJ
flr-135	24	5	studies	study	NOUN
flr-135	24	6	have	have	AUX
flr-135	24	7	shown	show	VERB
flr-135	24	8	the	the	DET
flr-135	24	9	applicability	applicability	NOUN
flr-135	24	10	and	and	CCONJ
flr-135	24	11	use	use	NOUN
flr-135	24	12	of	of	ADP
flr-135	24	13	this	this	DET
flr-135	24	14	methodology	methodology	NOUN
flr-135	24	15	in	in	ADP
flr-135	24	16	education	education	NOUN
flr-135	24	17	(	(	PUNCT
flr-135	24	18	e.g.	e.g.	ADV
flr-135	24	19	,	,	PUNCT
flr-135	24	20	cascallar	cascallar	ADJ
flr-135	24	21	,	,	PUNCT
flr-135	24	22	boekaerts	boekaert	NOUN
flr-135	24	23	,	,	PUNCT
flr-135	24	24	&	&	CCONJ
flr-135	24	25	costigan	costigan	NOUN
flr-135	24	26	,	,	PUNCT
flr-135	24	27	2006	2006	NUM
flr-135	24	28	;	;	PUNCT
flr-135	24	29	kyndt	kyndt	PROPN
flr-135	24	30	,	,	PUNCT
flr-135	24	31	musso	musso	PROPN
flr-135	24	32	,	,	PUNCT
flr-135	24	33	cascallar	cascallar	ADJ
flr-135	24	34	,	,	PUNCT
flr-135	24	35	&	&	CCONJ
flr-135	24	36	dochy	dochy	NOUN
flr-135	24	37	,	,	PUNCT
flr-135	24	38	2011	2011	NUM
flr-135	24	39	;	;	PUNCT
flr-135	24	40	kyndt	kyndt	PROPN
flr-135	24	41	,	,	PUNCT
flr-135	24	42	musso	musso	PROPN
flr-135	24	43	,	,	PUNCT
flr-135	24	44	cascallar	cascallar	ADJ
flr-135	24	45	,	,	PUNCT
flr-135	24	46	&	&	CCONJ
flr-135	24	47	dochy	dochy	NOUN
flr-135	24	48	,	,	PUNCT
flr-135	24	49	2015	2015	NUM
flr-135	24	50	;	;	PUNCT
flr-135	24	51	musso	musso	PROPN
flr-135	24	52	&	&	CCONJ
flr-135	24	53	cascallar	cascallar	ADJ
flr-135	24	54	,	,	PUNCT
flr-135	24	55	2009a	2009a	NUM
flr-135	24	56	;	;	PUNCT
flr-135	24	57	musso	musso	PROPN
flr-135	24	58	&	&	CCONJ
flr-135	24	59	cascallar	cascallar	ADJ
flr-135	24	60	,	,	PUNCT
flr-135	24	61	2009b	2009b	NOUN
flr-135	24	62	;	;	PUNCT
flr-135	24	63	musso	musso	PROPN
flr-135	24	64	,	,	PUNCT
flr-135	24	65	kyndt	kyndt	PROPN
flr-135	24	66	,	,	PUNCT
flr-135	24	67	cascallar	cascallar	ADJ
flr-135	24	68	&	&	CCONJ
flr-135	24	69	dochy	dochy	NOUN
flr-135	24	70	,	,	PUNCT
flr-135	24	71	2012	2012	NUM
flr-135	24	72	;	;	PUNCT
flr-135	24	73	musso	musso	PROPN
flr-135	24	74	et	et	PROPN
flr-135	24	75	al	al	PROPN
flr-135	24	76	.	.	PROPN
flr-135	24	77	,	,	PUNCT
flr-135	24	78	2013	2013	NUM
flr-135	24	79	;	;	PUNCT
flr-135	24	80	pinninghoff	pinninghoff	PROPN
flr-135	24	81	junemann	junemann	PROPN
flr-135	24	82	,	,	PUNCT
flr-135	24	83	salcedo	salcedo	PROPN
flr-135	24	84	lagos	lagos	PROPN
flr-135	24	85	,	,	PUNCT
flr-135	24	86	&	&	CCONJ
flr-135	24	87	contreras	contreras	PROPN
flr-135	24	88	arriagada	arriagada	PROPN
flr-135	24	89	,	,	PUNCT
flr-135	24	90	2007	2007	NUM
flr-135	24	91	;	;	PUNCT
flr-135	24	92	ramaswami	ramaswami	NOUN
flr-135	24	93	&	&	CCONJ
flr-135	24	94	bhaskaran	bhaskaran	NOUN
flr-135	24	95	,	,	PUNCT
flr-135	24	96	2010	2010	NUM
flr-135	24	97	;	;	PUNCT
flr-135	24	98	zambrano	zambrano	PROPN
flr-135	24	99	matamala	matamala	PROPN
flr-135	24	100	,	,	PUNCT
flr-135	24	101	rojas	rojas	PROPN
flr-135	24	102	díaz	díaz	NOUN
flr-135	24	103	,	,	PUNCT
flr-135	24	104	carvajal	carvajal	PROPN
flr-135	24	105	cuello	cuello	PROPN
flr-135	24	106	,	,	PUNCT
flr-135	24	107	&	&	CCONJ
flr-135	24	108	acuña	acuña	PROPN
flr-135	24	109	leiva	leiva	PROPN
flr-135	24	110	,	,	PUNCT
flr-135	24	111	2011	2011	NUM
flr-135	24	112	)	)	PUNCT
flr-135	24	113	.	.	PUNCT
flr-135	25	1	these	these	DET
flr-135	25	2	recent	recent	ADJ
flr-135	25	3	studies	study	NOUN
flr-135	25	4	have	have	AUX
flr-135	25	5	used	use	VERB
flr-135	25	6	anns	anns	NOUN
flr-135	25	7	both	both	PRON
flr-135	25	8	for	for	ADP
flr-135	25	9	prediction	prediction	NOUN
flr-135	25	10	/	/	SYM
flr-135	25	11	classification	classification	NOUN
flr-135	25	12	as	as	ADV
flr-135	25	13	well	well	ADV
flr-135	25	14	as	as	ADP
flr-135	25	15	for	for	ADP
flr-135	25	16	the	the	DET
flr-135	25	17	understanding	understanding	NOUN
flr-135	25	18	of	of	ADP
flr-135	25	19	the	the	DET
flr-135	25	20	underlying	underlying	ADJ
flr-135	25	21	variables	variable	NOUN
flr-135	25	22	involved	involve	VERB
flr-135	25	23	in	in	ADP
flr-135	25	24	the	the	DET
flr-135	25	25	educational	educational	ADJ
flr-135	25	26	outcomes	outcome	NOUN
flr-135	25	27	studied	study	VERB
flr-135	25	28	.	.	PUNCT
flr-135	26	1	now	now	ADV
flr-135	26	2	it	it	PRON
flr-135	26	3	cascallar	cascallar	ADJ
flr-135	26	4	et	et	NOUN
flr-135	26	5	al	al	PROPN
flr-135	26	6	69	69	NUM
flr-135	27	1	|	|	INTJ
flr-135	27	2	f	f	NOUN
flr-135	27	3	l	l	NOUN
flr-135	27	4	r	r	NOUN
flr-135	27	5	is	be	AUX
flr-135	27	6	important	important	ADJ
flr-135	27	7	to	to	PART
flr-135	27	8	show	show	VERB
flr-135	27	9	that	that	SCONJ
flr-135	27	10	recent	recent	ADJ
flr-135	27	11	advances	advance	NOUN
flr-135	27	12	in	in	ADP
flr-135	27	13	ann	ann	PROPN
flr-135	27	14	analysis	analysis	NOUN
flr-135	27	15	have	have	AUX
flr-135	27	16	addressed	address	VERB
flr-135	27	17	the	the	DET
flr-135	27	18	main	main	ADJ
flr-135	27	19	concerns	concern	NOUN
flr-135	27	20	expressed	express	VERB
flr-135	27	21	in	in	ADP
flr-135	27	22	edelsbrunner	edelsbrunner	NOUN
flr-135	27	23	&	&	CCONJ
flr-135	27	24	schneider	schneider	PROPN
flr-135	27	25	(	(	PUNCT
flr-135	27	26	2013	2013	NUM
flr-135	27	27	)	)	PUNCT
flr-135	27	28	.	.	PUNCT
flr-135	28	1	first	first	ADV
flr-135	28	2	,	,	PUNCT
flr-135	28	3	the	the	DET
flr-135	28	4	concerns	concern	NOUN
flr-135	28	5	regarding	regard	VERB
flr-135	28	6	the	the	DET
flr-135	28	7	presumed	presume	VERB
flr-135	28	8	“	"	PUNCT
flr-135	28	9	opacity	opacity	NOUN
flr-135	28	10	”	"	PUNCT
flr-135	28	11	of	of	ADP
flr-135	28	12	ann	ann	PROPN
flr-135	28	13	in	in	ADP
flr-135	28	14	terms	term	NOUN
flr-135	28	15	of	of	ADP
flr-135	28	16	their	their	PRON
flr-135	28	17	input	input	NOUN
flr-135	28	18	-	-	PUNCT
flr-135	28	19	output	output	NOUN
flr-135	28	20	relationships	relationship	NOUN
flr-135	28	21	will	will	AUX
flr-135	28	22	be	be	AUX
flr-135	28	23	addressed	address	VERB
flr-135	28	24	.	.	PUNCT
flr-135	29	1	the	the	DET
flr-135	29	2	authors	author	NOUN
flr-135	29	3	undermine	undermine	VERB
flr-135	29	4	their	their	PRON
flr-135	29	5	own	own	ADJ
flr-135	29	6	estimate	estimate	NOUN
flr-135	29	7	of	of	ADP
flr-135	29	8	the	the	DET
flr-135	29	9	value	value	NOUN
flr-135	29	10	of	of	ADP
flr-135	29	11	anns	anns	NOUN
flr-135	29	12	as	as	ADP
flr-135	29	13	a	a	DET
flr-135	29	14	“	"	PUNCT
flr-135	29	15	promising	promising	ADJ
flr-135	29	16	technique	technique	NOUN
flr-135	29	17	”	"	PUNCT
flr-135	29	18	by	by	ADP
flr-135	29	19	essentially	essentially	ADV
flr-135	29	20	arguing	argue	VERB
flr-135	29	21	that	that	SCONJ
flr-135	29	22	it	it	PRON
flr-135	29	23	is	be	AUX
flr-135	29	24	contrary	contrary	ADJ
flr-135	29	25	to	to	ADP
flr-135	29	26	good	good	ADJ
flr-135	29	27	scientific	scientific	ADJ
flr-135	29	28	practice	practice	NOUN
flr-135	29	29	for	for	ADP
flr-135	29	30	theory	theory	NOUN
flr-135	29	31	-	-	PUNCT
flr-135	29	32	building	building	NOUN
flr-135	29	33	given	give	VERB
flr-135	29	34	the	the	DET
flr-135	29	35	presumed	presume	VERB
flr-135	29	36	“	"	PUNCT
flr-135	29	37	opaque	opaque	ADJ
flr-135	29	38	”	"	PUNCT
flr-135	29	39	nature	nature	NOUN
flr-135	29	40	of	of	ADP
flr-135	29	41	their	their	PRON
flr-135	29	42	internal	internal	ADJ
flr-135	29	43	structure	structure	NOUN
flr-135	29	44	which	which	PRON
flr-135	29	45	makes	make	VERB
flr-135	29	46	interpretation	interpretation	NOUN
flr-135	29	47	difficult	difficult	ADJ
flr-135	29	48	if	if	SCONJ
flr-135	29	49	not	not	PART
flr-135	29	50	impossible	impossible	ADJ
flr-135	29	51	.	.	PUNCT
flr-135	30	1	the	the	DET
flr-135	30	2	often	often	ADV
flr-135	30	3	and	and	CCONJ
flr-135	30	4	now	now	ADV
flr-135	30	5	quite	quite	ADV
flr-135	30	6	outdated	outdated	ADJ
flr-135	30	7	argument	argument	NOUN
flr-135	30	8	of	of	ADP
flr-135	30	9	anns	anns	NOUN
flr-135	30	10	as	as	ADP
flr-135	30	11	“	"	PUNCT
flr-135	30	12	black	black	ADJ
flr-135	30	13	boxes	box	NOUN
flr-135	30	14	”	"	PUNCT
flr-135	30	15	(	(	PUNCT
flr-135	30	16	cf	cf	NOUN
flr-135	30	17	.	.	PUNCT
flr-135	30	18	benitez	benitez	PROPN
flr-135	30	19	,	,	PUNCT
flr-135	30	20	castro	castro	PROPN
flr-135	30	21	&	&	CCONJ
flr-135	30	22	requena	requena	PROPN
flr-135	30	23	,	,	PUNCT
flr-135	30	24	1997	1997	NUM
flr-135	30	25	)	)	PUNCT
flr-135	30	26	is	be	AUX
flr-135	30	27	therefore	therefore	ADV
flr-135	30	28	raised	raise	VERB
flr-135	30	29	once	once	ADV
flr-135	30	30	again	again	ADV
flr-135	30	31	.	.	PUNCT
flr-135	31	1	however	however	ADV
flr-135	31	2	,	,	PUNCT
flr-135	31	3	these	these	DET
flr-135	31	4	arguments	argument	NOUN
flr-135	31	5	are	be	AUX
flr-135	31	6	raised	raise	VERB
flr-135	31	7	ignoring	ignore	VERB
flr-135	31	8	the	the	DET
flr-135	31	9	vast	vast	ADJ
flr-135	31	10	amount	amount	NOUN
flr-135	31	11	of	of	ADP
flr-135	31	12	research	research	NOUN
flr-135	31	13	that	that	PRON
flr-135	31	14	has	have	AUX
flr-135	31	15	been	be	AUX
flr-135	31	16	going	go	VERB
flr-135	31	17	on	on	ADP
flr-135	31	18	in	in	ADP
flr-135	31	19	this	this	DET
flr-135	31	20	field	field	NOUN
flr-135	31	21	to	to	PART
flr-135	31	22	overcome	overcome	VERB
flr-135	31	23	this	this	DET
flr-135	31	24	initial	initial	ADJ
flr-135	31	25	drawback	drawback	NOUN
flr-135	31	26	of	of	ADP
flr-135	31	27	predictive	predictive	ADJ
flr-135	31	28	systems	system	NOUN
flr-135	31	29	analyses	analysis	NOUN
flr-135	31	30	(	(	PUNCT
flr-135	31	31	e.g.	e.g.	ADV
flr-135	31	32	,	,	PUNCT
flr-135	31	33	frey	frey	PROPN
flr-135	31	34	&	&	CCONJ
flr-135	31	35	rusch	rusch	PROPN
flr-135	31	36	,	,	PUNCT
flr-135	31	37	2013	2013	NUM
flr-135	31	38	;	;	PUNCT
flr-135	31	39	intrator	intrator	NOUN
flr-135	31	40	&	&	CCONJ
flr-135	31	41	intrator	intrator	PROPN
flr-135	31	42	,	,	PUNCT
flr-135	31	43	2001	2001	NUM
flr-135	31	44	;	;	PUNCT
flr-135	31	45	lee	lee	PROPN
flr-135	31	46	,	,	PUNCT
flr-135	31	47	rey	rey	PROPN
flr-135	31	48	,	,	PUNCT
flr-135	31	49	mentele	mentele	PROPN
flr-135	31	50	,	,	PUNCT
flr-135	31	51	&	&	CCONJ
flr-135	31	52	garver	garver	NOUN
flr-135	31	53	,	,	PUNCT
flr-135	31	54	2005	2005	NUM
flr-135	31	55	;	;	PUNCT
flr-135	31	56	tzeng	tzeng	PROPN
flr-135	31	57	&	&	CCONJ
flr-135	31	58	ma	ma	PROPN
flr-135	31	59	,	,	PUNCT
flr-135	31	60	2005	2005	NUM
flr-135	31	61	;	;	PUNCT
flr-135	31	62	yeh	yeh	PROPN
flr-135	31	63	&	&	CCONJ
flr-135	31	64	cheng	cheng	PROPN
flr-135	31	65	2010	2010	NUM
flr-135	31	66	)	)	PUNCT
flr-135	31	67	.	.	PUNCT
flr-135	32	1	considering	consider	VERB
flr-135	32	2	the	the	DET
flr-135	32	3	nature	nature	NOUN
flr-135	32	4	and	and	CCONJ
flr-135	32	5	centrality	centrality	NOUN
flr-135	32	6	of	of	ADP
flr-135	32	7	modelling	modelling	NOUN
flr-135	32	8	in	in	ADP
flr-135	32	9	science	science	NOUN
flr-135	32	10	,	,	PUNCT
flr-135	32	11	as	as	SCONJ
flr-135	32	12	was	be	AUX
flr-135	32	13	clearly	clearly	ADV
flr-135	32	14	presented	present	VERB
flr-135	32	15	by	by	ADP
flr-135	32	16	frigg	frigg	PROPN
flr-135	32	17	and	and	CCONJ
flr-135	32	18	hartmann	hartmann	PROPN
flr-135	32	19	(	(	PUNCT
flr-135	32	20	2006	2006	NUM
flr-135	32	21	)	)	PUNCT
flr-135	32	22	,	,	PUNCT
flr-135	32	23	models	model	NOUN
flr-135	32	24	can	can	AUX
flr-135	32	25	perform	perform	VERB
flr-135	32	26	two	two	NUM
flr-135	32	27	different	different	ADJ
flr-135	32	28	representational	representational	ADJ
flr-135	32	29	functions	function	NOUN
flr-135	32	30	,	,	PUNCT
flr-135	32	31	which	which	PRON
flr-135	32	32	are	be	AUX
flr-135	32	33	not	not	PART
flr-135	32	34	mutually	mutually	ADV
flr-135	32	35	exclusive	exclusive	ADJ
flr-135	32	36	as	as	ADP
flr-135	32	37	scientific	scientific	ADJ
flr-135	32	38	models	model	NOUN
flr-135	32	39	.	.	PUNCT
flr-135	33	1	first	first	ADV
flr-135	33	2	,	,	PUNCT
flr-135	33	3	they	they	PRON
flr-135	33	4	can	can	AUX
flr-135	33	5	be	be	AUX
flr-135	33	6	a	a	DET
flr-135	33	7	representation	representation	NOUN
flr-135	33	8	of	of	ADP
flr-135	33	9	an	an	DET
flr-135	33	10	aspect	aspect	NOUN
flr-135	33	11	or	or	CCONJ
flr-135	33	12	selected	select	VERB
flr-135	33	13	part	part	NOUN
flr-135	33	14	of	of	ADP
flr-135	33	15	the	the	DET
flr-135	33	16	world	world	NOUN
flr-135	33	17	,	,	PUNCT
flr-135	33	18	what	what	PRON
flr-135	33	19	they	they	PRON
flr-135	33	20	call	call	VERB
flr-135	33	21	the	the	DET
flr-135	33	22	“	"	PUNCT
flr-135	33	23	target	target	NOUN
flr-135	33	24	system	system	NOUN
flr-135	33	25	”	"	PUNCT
flr-135	33	26	.	.	PUNCT
flr-135	34	1	in	in	ADP
flr-135	34	2	this	this	DET
flr-135	34	3	case	case	NOUN
flr-135	34	4	,	,	PUNCT
flr-135	34	5	what	what	PRON
flr-135	34	6	can	can	AUX
flr-135	34	7	be	be	AUX
flr-135	34	8	modelled	model	VERB
flr-135	34	9	are	be	AUX
flr-135	34	10	either	either	CCONJ
flr-135	34	11	phenomena	phenomenon	NOUN
flr-135	34	12	or	or	CCONJ
flr-135	34	13	data	datum	NOUN
flr-135	34	14	.	.	PUNCT
flr-135	35	1	the	the	DET
flr-135	35	2	second	second	ADJ
flr-135	35	3	notion	notion	NOUN
flr-135	35	4	of	of	ADP
flr-135	35	5	modelling	modelling	NOUN
flr-135	35	6	is	be	AUX
flr-135	35	7	the	the	DET
flr-135	35	8	representation	representation	NOUN
flr-135	35	9	of	of	ADP
flr-135	35	10	a	a	DET
flr-135	35	11	theory	theory	NOUN
flr-135	35	12	in	in	ADP
flr-135	35	13	that	that	SCONJ
flr-135	35	14	it	it	PRON
flr-135	35	15	represents	represent	VERB
flr-135	35	16	its	its	PRON
flr-135	35	17	rules	rule	NOUN
flr-135	35	18	,	,	PUNCT
flr-135	35	19	laws	law	NOUN
flr-135	35	20	and	and	CCONJ
flr-135	35	21	axioms	axiom	NOUN
flr-135	35	22	.	.	PUNCT
flr-135	36	1	clearly	clearly	ADV
flr-135	36	2	,	,	PUNCT
flr-135	36	3	anns	ann	NOUN
flr-135	36	4	contribute	contribute	VERB
flr-135	36	5	to	to	ADP
flr-135	36	6	the	the	DET
flr-135	36	7	construction	construction	NOUN
flr-135	36	8	of	of	ADP
flr-135	36	9	better	well	ADJ
flr-135	36	10	representational	representational	ADJ
flr-135	36	11	models	model	NOUN
flr-135	36	12	consisting	consist	VERB
flr-135	36	13	of	of	ADP
flr-135	36	14	“	"	PUNCT
flr-135	36	15	models	model	NOUN
flr-135	36	16	of	of	ADP
flr-135	36	17	data	datum	NOUN
flr-135	36	18	”	"	PUNCT
flr-135	36	19	(	(	PUNCT
flr-135	36	20	suppes	suppe	NOUN
flr-135	36	21	,	,	PUNCT
flr-135	36	22	1962	1962	NUM
flr-135	36	23	)	)	PUNCT
flr-135	36	24	.	.	PUNCT
flr-135	37	1	in	in	ADP
flr-135	37	2	particular	particular	ADJ
flr-135	37	3	,	,	PUNCT
flr-135	37	4	this	this	DET
flr-135	37	5	contribution	contribution	NOUN
flr-135	37	6	is	be	AUX
flr-135	37	7	based	base	VERB
flr-135	37	8	on	on	ADP
flr-135	37	9	ample	ample	ADJ
flr-135	37	10	research	research	NOUN
flr-135	37	11	that	that	PRON
flr-135	37	12	has	have	AUX
flr-135	37	13	been	be	AUX
flr-135	37	14	crucial	crucial	ADJ
flr-135	37	15	in	in	ADP
flr-135	37	16	making	make	VERB
flr-135	37	17	the	the	DET
flr-135	37	18	link	link	NOUN
flr-135	37	19	between	between	ADP
flr-135	37	20	anns	anns	NOUN
flr-135	37	21	representations	representation	NOUN
flr-135	37	22	and	and	CCONJ
flr-135	37	23	their	their	PRON
flr-135	37	24	relationship	relationship	NOUN
flr-135	37	25	to	to	ADP
flr-135	37	26	the	the	DET
flr-135	37	27	obtained	obtain	VERB
flr-135	37	28	outputs	output	NOUN
flr-135	37	29	.	.	PUNCT
flr-135	38	1	as	as	ADP
flr-135	38	2	an	an	DET
flr-135	38	3	anecdote	anecdote	NOUN
flr-135	38	4	,	,	PUNCT
flr-135	38	5	it	it	PRON
flr-135	38	6	is	be	AUX
flr-135	38	7	interesting	interesting	ADJ
flr-135	38	8	and	and	CCONJ
flr-135	38	9	revealing	reveal	VERB
flr-135	38	10	that	that	DET
flr-135	38	11	edelsbrunner	edelsbrunner	NOUN
flr-135	38	12	and	and	CCONJ
flr-135	38	13	schneider	schneider	NOUN
flr-135	38	14	(	(	PUNCT
flr-135	38	15	2013	2013	NUM
flr-135	38	16	)	)	PUNCT
flr-135	38	17	cite	cite	VERB
flr-135	38	18	the	the	DET
flr-135	38	19	paper	paper	NOUN
flr-135	38	20	of	of	ADP
flr-135	38	21	benitez	benitez	PROPN
flr-135	38	22	,	,	PUNCT
flr-135	38	23	et	et	PROPN
flr-135	38	24	al	al	PROPN
flr-135	38	25	.	.	PROPN
flr-135	39	1	(	(	PUNCT
flr-135	39	2	1997	1997	NUM
flr-135	39	3	)	)	PUNCT
flr-135	39	4	which	which	PRON
flr-135	39	5	presents	present	VERB
flr-135	39	6	an	an	DET
flr-135	39	7	addition	addition	NOUN
flr-135	39	8	to	to	ADP
flr-135	39	9	the	the	DET
flr-135	39	10	usual	usual	ADJ
flr-135	39	11	ann	ann	PROPN
flr-135	39	12	techniques	technique	NOUN
flr-135	39	13	which	which	PRON
flr-135	39	14	according	accord	VERB
flr-135	39	15	to	to	ADP
flr-135	39	16	benitez	benitez	PROPN
flr-135	39	17	et	et	PROPN
flr-135	39	18	al	al	PROPN
flr-135	39	19	.	.	PROPN
flr-135	40	1	(	(	PUNCT
flr-135	40	2	1997	1997	NUM
flr-135	40	3	)	)	PUNCT
flr-135	40	4	provide	provide	VERB
flr-135	40	5	“	"	PUNCT
flr-135	40	6	such	such	DET
flr-135	40	7	an	an	DET
flr-135	40	8	interpretation	interpretation	NOUN
flr-135	40	9	of	of	ADP
flr-135	40	10	neural	neural	ADJ
flr-135	40	11	networks	network	NOUN
flr-135	40	12	so	so	SCONJ
flr-135	40	13	that	that	SCONJ
flr-135	40	14	they	they	PRON
flr-135	40	15	will	will	AUX
flr-135	40	16	no	no	ADV
flr-135	40	17	longer	long	ADV
flr-135	40	18	be	be	AUX
flr-135	40	19	seen	see	VERB
flr-135	40	20	as	as	ADP
flr-135	40	21	black	black	ADJ
flr-135	40	22	boxes	box	NOUN
flr-135	40	23	”	"	PUNCT
flr-135	40	24	(	(	PUNCT
flr-135	40	25	p.	p.	NOUN
flr-135	40	26	1156	1156	NUM
flr-135	40	27	)	)	PUNCT
flr-135	40	28	,	,	PUNCT
flr-135	40	29	which	which	PRON
flr-135	40	30	clearly	clearly	ADV
flr-135	40	31	contradicts	contradict	VERB
flr-135	40	32	the	the	DET
flr-135	40	33	use	use	NOUN
flr-135	40	34	of	of	ADP
flr-135	40	35	the	the	DET
flr-135	40	36	article	article	NOUN
flr-135	40	37	of	of	ADP
flr-135	40	38	benitez	benitez	PROPN
flr-135	40	39	et	et	PROPN
flr-135	40	40	al	al	PROPN
flr-135	40	41	.	.	PROPN
flr-135	41	1	(	(	PUNCT
flr-135	41	2	1997	1997	NUM
flr-135	41	3	)	)	PUNCT
flr-135	41	4	as	as	ADP
flr-135	41	5	supporting	support	VERB
flr-135	41	6	the	the	DET
flr-135	41	7	“	"	PUNCT
flr-135	41	8	black	black	ADJ
flr-135	41	9	box	box	NOUN
flr-135	41	10	”	"	PUNCT
flr-135	41	11	unique	unique	ADJ
flr-135	41	12	perception	perception	NOUN
flr-135	41	13	of	of	ADP
flr-135	41	14	anns	ann	NOUN
flr-135	41	15	.	.	PUNCT
flr-135	42	1	the	the	DET
flr-135	42	2	proposed	propose	VERB
flr-135	42	3	approach	approach	NOUN
flr-135	42	4	,	,	PUNCT
flr-135	42	5	in	in	ADP
flr-135	42	6	this	this	DET
flr-135	42	7	case	case	NOUN
flr-135	42	8	is	be	AUX
flr-135	42	9	based	base	VERB
flr-135	42	10	on	on	ADP
flr-135	42	11	the	the	DET
flr-135	42	12	determination	determination	NOUN
flr-135	42	13	of	of	ADP
flr-135	42	14	the	the	DET
flr-135	42	15	equality	equality	NOUN
flr-135	42	16	between	between	ADP
flr-135	42	17	multilayered	multilayered	ADJ
flr-135	42	18	perceptron	perceptron	PROPN
flr-135	42	19	anns	anns	PROPN
flr-135	42	20	,	,	PUNCT
flr-135	42	21	precisely	precisely	ADV
flr-135	42	22	the	the	DET
flr-135	42	23	one	one	NOUN
flr-135	42	24	used	use	VERB
flr-135	42	25	by	by	ADP
flr-135	42	26	musso	musso	PROPN
flr-135	42	27	et	et	PROPN
flr-135	42	28	al	al	PROPN
flr-135	42	29	.	.	PROPN
flr-135	43	1	(	(	PUNCT
flr-135	43	2	2013	2013	NUM
flr-135	43	3	)	)	PUNCT
flr-135	43	4	,	,	PUNCT
flr-135	43	5	and	and	CCONJ
flr-135	43	6	fuzzy	fuzzy	ADJ
flr-135	43	7	rule	rule	NOUN
flr-135	43	8	-	-	PUNCT
flr-135	43	9	based	base	VERB
flr-135	43	10	systems	system	NOUN
flr-135	43	11	.	.	PUNCT
flr-135	44	1	the	the	DET
flr-135	44	2	operator	operator	NOUN
flr-135	44	3	derived	derive	VERB
flr-135	44	4	from	from	ADP
flr-135	44	5	this	this	DET
flr-135	44	6	equivalency	equivalency	NOUN
flr-135	44	7	concept	concept	NOUN
flr-135	44	8	results	result	NOUN
flr-135	44	9	in	in	ADP
flr-135	44	10	the	the	DET
flr-135	44	11	transformation	transformation	NOUN
flr-135	44	12	of	of	ADP
flr-135	44	13	fuzzy	fuzzy	ADJ
flr-135	44	14	rules	rule	NOUN
flr-135	44	15	into	into	ADP
flr-135	44	16	a	a	DET
flr-135	44	17	format	format	NOUN
flr-135	44	18	which	which	PRON
flr-135	44	19	can	can	AUX
flr-135	44	20	be	be	AUX
flr-135	44	21	easily	easily	ADV
flr-135	44	22	understood	understand	VERB
flr-135	44	23	.	.	PUNCT
flr-135	45	1	thus	thus	ADV
flr-135	45	2	,	,	PUNCT
flr-135	45	3	the	the	DET
flr-135	45	4	knowledge	knowledge	NOUN
flr-135	45	5	generated	generate	VERB
flr-135	45	6	by	by	ADP
flr-135	45	7	the	the	DET
flr-135	45	8	ann	ann	PROPN
flr-135	45	9	after	after	SCONJ
flr-135	45	10	the	the	DET
flr-135	45	11	learning	learning	NOUN
flr-135	45	12	process	process	NOUN
flr-135	45	13	is	be	AUX
flr-135	45	14	finished	finish	VERB
flr-135	45	15	can	can	AUX
flr-135	45	16	be	be	AUX
flr-135	45	17	more	more	ADV
flr-135	45	18	easily	easily	ADV
flr-135	45	19	and	and	CCONJ
flr-135	45	20	clearly	clearly	ADV
flr-135	45	21	explained	explain	VERB
flr-135	45	22	,	,	PUNCT
flr-135	45	23	“	"	PUNCT
flr-135	45	24	so	so	SCONJ
flr-135	45	25	that	that	SCONJ
flr-135	45	26	they	they	PRON
flr-135	45	27	can	can	AUX
flr-135	45	28	no	no	ADV
flr-135	45	29	longer	long	ADV
flr-135	45	30	be	be	AUX
flr-135	45	31	considered	consider	VERB
flr-135	45	32	as	as	ADP
flr-135	45	33	black	black	ADJ
flr-135	45	34	boxes	box	NOUN
flr-135	45	35	”	"	PUNCT
flr-135	45	36	(	(	PUNCT
flr-135	45	37	benitez	benitez	PROPN
flr-135	45	38	et	et	PROPN
flr-135	45	39	al	al	PROPN
flr-135	45	40	.	.	PROPN
flr-135	45	41	,	,	PUNCT
flr-135	45	42	1997	1997	NUM
flr-135	45	43	,	,	PUNCT
flr-135	45	44	p.	p.	NOUN
flr-135	45	45	1156	1156	NUM
flr-135	45	46	)	)	PUNCT
flr-135	45	47	,	,	PUNCT
flr-135	45	48	while	while	SCONJ
flr-135	45	49	retaining	retain	VERB
flr-135	45	50	all	all	DET
flr-135	45	51	the	the	DET
flr-135	45	52	advantages	advantage	NOUN
flr-135	45	53	and	and	CCONJ
flr-135	45	54	power	power	NOUN
flr-135	45	55	of	of	ADP
flr-135	45	56	the	the	DET
flr-135	45	57	anns	anns	NOUN
flr-135	45	58	as	as	ADP
flr-135	45	59	very	very	ADV
flr-135	45	60	efficient	efficient	ADJ
flr-135	45	61	computing	computing	NOUN
flr-135	45	62	representations	representation	NOUN
flr-135	45	63	as	as	ADP
flr-135	45	64	automated	automate	VERB
flr-135	45	65	knowledge	knowledge	NOUN
flr-135	45	66	acquisition	acquisition	NOUN
flr-135	45	67	procedure	procedure	NOUN
flr-135	45	68	models	model	NOUN
flr-135	45	69	,	,	PUNCT
flr-135	45	70	and	and	CCONJ
flr-135	45	71	as	as	ADP
flr-135	45	72	universal	universal	ADJ
flr-135	45	73	approximators	approximator	NOUN
flr-135	45	74	(	(	PUNCT
flr-135	45	75	ripley	ripley	PROPN
flr-135	45	76	,	,	PUNCT
flr-135	45	77	1996	1996	NUM
flr-135	45	78	)	)	PUNCT
flr-135	45	79	.	.	PUNCT
flr-135	46	1	in	in	ADP
flr-135	46	2	fact	fact	NOUN
flr-135	46	3	,	,	PUNCT
flr-135	46	4	west	west	PROPN
flr-135	46	5	,	,	PUNCT
flr-135	46	6	brockett	brockett	PROPN
flr-135	46	7	,	,	PUNCT
flr-135	46	8	and	and	CCONJ
flr-135	46	9	golden	golden	ADJ
flr-135	46	10	(	(	PUNCT
flr-135	46	11	1997	1997	NUM
flr-135	46	12	)	)	PUNCT
flr-135	46	13	state	state	NOUN
flr-135	46	14	that	that	SCONJ
flr-135	46	15	neural	neural	ADJ
flr-135	46	16	networks	network	NOUN
flr-135	46	17	“	"	PUNCT
flr-135	46	18	are	be	AUX
flr-135	46	19	a	a	DET
flr-135	46	20	well	well	ADV
flr-135	46	21	-	-	PUNCT
flr-135	46	22	defined	define	VERB
flr-135	46	23	adaptive	adaptive	ADJ
flr-135	46	24	gradient	gradient	NOUN
flr-135	46	25	search	search	NOUN
flr-135	46	26	procedure	procedure	NOUN
flr-135	46	27	for	for	ADP
flr-135	46	28	parameter	parameter	NOUN
flr-135	46	29	fitting	fit	VERB
flr-135	46	30	in	in	ADP
flr-135	46	31	a	a	DET
flr-135	46	32	complex	complex	ADJ
flr-135	46	33	nonlinear	nonlinear	ADJ
flr-135	46	34	model	model	NOUN
flr-135	46	35	,	,	PUNCT
flr-135	46	36	and	and	CCONJ
flr-135	46	37	not	not	PART
flr-135	46	38	a	a	DET
flr-135	46	39	„	„	PUNCT
flr-135	46	40	black	black	ADJ
flr-135	46	41	box‟	box‟	PROPN
flr-135	46	42	at	at	ADV
flr-135	46	43	all	all	ADV
flr-135	46	44	”	"	PUNCT
flr-135	46	45	(	(	PUNCT
flr-135	46	46	p.	p.	NOUN
flr-135	46	47	389	389	NUM
flr-135	46	48	)	)	PUNCT
flr-135	46	49	.	.	PUNCT
flr-135	47	1	in	in	ADP
flr-135	47	2	addition	addition	NOUN
flr-135	47	3	,	,	PUNCT
flr-135	47	4	the	the	DET
flr-135	47	5	efforts	effort	NOUN
flr-135	47	6	to	to	PART
flr-135	47	7	develop	develop	VERB
flr-135	47	8	better	well	ADJ
flr-135	47	9	and	and	CCONJ
flr-135	47	10	more	more	ADV
flr-135	47	11	comprehensive	comprehensive	ADJ
flr-135	47	12	visualisation	visualisation	NOUN
flr-135	47	13	techniques	technique	NOUN
flr-135	47	14	for	for	ADP
flr-135	47	15	the	the	DET
flr-135	47	16	complex	complex	ADJ
flr-135	47	17	interactions	interaction	NOUN
flr-135	47	18	in	in	ADP
flr-135	47	19	an	an	DET
flr-135	47	20	ann	ann	PROPN
flr-135	47	21	,	,	PUNCT
flr-135	47	22	such	such	ADJ
flr-135	47	23	as	as	ADP
flr-135	47	24	those	those	PRON
flr-135	47	25	suggested	suggest	VERB
flr-135	47	26	by	by	ADP
flr-135	47	27	tzeng	tzeng	PROPN
flr-135	47	28	and	and	CCONJ
flr-135	47	29	ma	ma	PROPN
flr-135	47	30	(	(	PUNCT
flr-135	47	31	2005	2005	NUM
flr-135	47	32	)	)	PUNCT
flr-135	47	33	have	have	AUX
flr-135	47	34	contributed	contribute	VERB
flr-135	47	35	to	to	PART
flr-135	47	36	open	open	VERB
flr-135	47	37	the	the	DET
flr-135	47	38	“	"	PUNCT
flr-135	47	39	black	black	ADJ
flr-135	47	40	box	box	NOUN
flr-135	47	41	”	"	PUNCT
flr-135	47	42	and	and	CCONJ
flr-135	47	43	help	help	VERB
flr-135	47	44	the	the	DET
flr-135	47	45	researcher	researcher	NOUN
flr-135	47	46	in	in	ADP
flr-135	47	47	determining	determine	VERB
flr-135	47	48	underlying	underlie	VERB
flr-135	47	49	dependencies	dependency	NOUN
flr-135	47	50	between	between	ADP
flr-135	47	51	inputs	input	NOUN
flr-135	47	52	and	and	CCONJ
flr-135	47	53	outputs	output	NOUN
flr-135	47	54	of	of	ADP
flr-135	47	55	a	a	DET
flr-135	47	56	neural	neural	ADJ
flr-135	47	57	network	network	NOUN
flr-135	47	58	.	.	PUNCT
flr-135	48	1	as	as	ADP
flr-135	48	2	a	a	DET
flr-135	48	3	consequence	consequence	NOUN
flr-135	48	4	,	,	PUNCT
flr-135	48	5	they	they	PRON
flr-135	48	6	do	do	AUX
flr-135	48	7	not	not	PART
flr-135	48	8	only	only	ADV
flr-135	48	9	facilitate	facilitate	VERB
flr-135	48	10	the	the	DET
flr-135	48	11	design	design	NOUN
flr-135	48	12	of	of	ADP
flr-135	48	13	efficient	efficient	ADJ
flr-135	48	14	anns	ann	NOUN
flr-135	48	15	,	,	PUNCT
flr-135	48	16	but	but	CCONJ
flr-135	48	17	also	also	ADV
flr-135	48	18	enable	enable	VERB
flr-135	48	19	the	the	DET
flr-135	48	20	use	use	NOUN
flr-135	48	21	of	of	ADP
flr-135	48	22	anns	anns	NOUN
flr-135	48	23	for	for	ADP
flr-135	48	24	problem	problem	NOUN
flr-135	48	25	solving	solving	NOUN
flr-135	48	26	.	.	PUNCT
flr-135	49	1	it	it	PRON
flr-135	49	2	is	be	AUX
flr-135	49	3	true	true	ADJ
flr-135	49	4	that	that	SCONJ
flr-135	49	5	cascallar	cascallar	ADJ
flr-135	49	6	et	et	NOUN
flr-135	49	7	al	al	PROPN
flr-135	49	8	70	70	NUM
flr-135	50	1	|	|	CCONJ
flr-135	50	2	f	f	NOUN
flr-135	50	3	l	l	NOUN
flr-135	50	4	r	r	NOUN
flr-135	50	5	visualisation	visualisation	NOUN
flr-135	50	6	is	be	AUX
flr-135	50	7	not	not	PART
flr-135	50	8	explanation	explanation	NOUN
flr-135	50	9	,	,	PUNCT
flr-135	50	10	but	but	CCONJ
flr-135	50	11	they	they	PRON
flr-135	50	12	are	be	AUX
flr-135	50	13	powerful	powerful	ADJ
flr-135	50	14	tools	tool	NOUN
flr-135	50	15	to	to	PART
flr-135	50	16	guide	guide	VERB
flr-135	50	17	the	the	DET
flr-135	50	18	refinement	refinement	NOUN
flr-135	50	19	of	of	ADP
flr-135	50	20	neural	neural	ADJ
flr-135	50	21	network	network	NOUN
flr-135	50	22	structures	structure	NOUN
flr-135	50	23	for	for	ADP
flr-135	50	24	problem	problem	NOUN
flr-135	50	25	solving	solving	NOUN
flr-135	50	26	(	(	PUNCT
flr-135	50	27	e.g.	e.g.	ADV
flr-135	50	28	,	,	PUNCT
flr-135	50	29	classification	classification	NOUN
flr-135	50	30	tasks	task	NOUN
flr-135	50	31	)	)	PUNCT
flr-135	50	32	using	use	VERB
flr-135	50	33	anns	ann	NOUN
flr-135	50	34	or	or	CCONJ
flr-135	50	35	other	other	ADJ
flr-135	50	36	machine	machine	NOUN
flr-135	50	37	learning	learning	NOUN
flr-135	50	38	models	model	NOUN
flr-135	50	39	.	.	PUNCT
flr-135	51	1	another	another	DET
flr-135	51	2	significant	significant	ADJ
flr-135	51	3	addition	addition	NOUN
flr-135	51	4	to	to	ADP
flr-135	51	5	the	the	DET
flr-135	51	6	literature	literature	NOUN
flr-135	51	7	which	which	PRON
flr-135	51	8	“	"	PUNCT
flr-135	51	9	opens	open	VERB
flr-135	51	10	the	the	DET
flr-135	51	11	box	box	NOUN
flr-135	51	12	”	"	PUNCT
flr-135	51	13	in	in	ADP
flr-135	51	14	ann	ann	PROPN
flr-135	51	15	analyses	analysis	NOUN
flr-135	51	16	is	be	AUX
flr-135	51	17	the	the	DET
flr-135	51	18	concept	concept	NOUN
flr-135	51	19	of	of	ADP
flr-135	51	20	structured	structured	ADJ
flr-135	51	21	neural	neural	ADJ
flr-135	51	22	network	network	NOUN
flr-135	51	23	(	(	PUNCT
flr-135	51	24	snn	snn	PROPN
flr-135	51	25	)	)	PUNCT
flr-135	51	26	techniques	technique	NOUN
flr-135	51	27	used	use	VERB
flr-135	51	28	for	for	ADP
flr-135	51	29	modelling	modelling	NOUN
flr-135	51	30	(	(	PUNCT
flr-135	51	31	lee	lee	PROPN
flr-135	51	32	,	,	PUNCT
flr-135	51	33	rey	rey	PROPN
flr-135	51	34	,	,	PUNCT
flr-135	51	35	mentele	mentele	PROPN
flr-135	51	36	,	,	PUNCT
flr-135	51	37	&	&	CCONJ
flr-135	51	38	garver	garver	NOUN
flr-135	51	39	,	,	PUNCT
flr-135	51	40	2005	2005	NUM
flr-135	51	41	)	)	PUNCT
flr-135	51	42	.	.	PUNCT
flr-135	52	1	in	in	ADP
flr-135	52	2	this	this	DET
flr-135	52	3	approach	approach	NOUN
flr-135	52	4	,	,	PUNCT
flr-135	52	5	the	the	DET
flr-135	52	6	actual	actual	ADJ
flr-135	52	7	construction	construction	NOUN
flr-135	52	8	of	of	ADP
flr-135	52	9	the	the	DET
flr-135	52	10	network	network	NOUN
flr-135	52	11	is	be	AUX
flr-135	52	12	based	base	VERB
flr-135	52	13	on	on	ADP
flr-135	52	14	existing	exist	VERB
flr-135	52	15	contextual	contextual	ADJ
flr-135	52	16	and	and	CCONJ
flr-135	52	17	theoretical	theoretical	ADJ
flr-135	52	18	knowledge	knowledge	NOUN
flr-135	52	19	to	to	PART
flr-135	52	20	assist	assist	VERB
flr-135	52	21	in	in	ADP
flr-135	52	22	the	the	DET
flr-135	52	23	design	design	NOUN
flr-135	52	24	of	of	ADP
flr-135	52	25	the	the	DET
flr-135	52	26	ann	ann	PROPN
flr-135	52	27	structure	structure	NOUN
flr-135	52	28	of	of	ADP
flr-135	52	29	inputs	input	NOUN
flr-135	52	30	.	.	PUNCT
flr-135	53	1	in	in	ADP
flr-135	53	2	fact	fact	NOUN
flr-135	53	3	,	,	PUNCT
flr-135	53	4	a	a	DET
flr-135	53	5	similar	similar	ADJ
flr-135	53	6	approach	approach	NOUN
flr-135	53	7	was	be	AUX
flr-135	53	8	followed	follow	VERB
flr-135	53	9	by	by	ADP
flr-135	53	10	musso	musso	PROPN
flr-135	53	11	et	et	PROPN
flr-135	53	12	al	al	PROPN
flr-135	53	13	.	.	PROPN
flr-135	54	1	(	(	PUNCT
flr-135	54	2	2013	2013	NUM
flr-135	54	3	)	)	PUNCT
flr-135	54	4	,	,	PUNCT
flr-135	54	5	by	by	ADP
flr-135	54	6	populating	populate	VERB
flr-135	54	7	the	the	DET
flr-135	54	8	inputs	input	NOUN
flr-135	54	9	based	base	VERB
flr-135	54	10	solely	solely	ADV
flr-135	54	11	on	on	ADP
flr-135	54	12	solid	solid	ADJ
flr-135	54	13	theoretical	theoretical	ADJ
flr-135	54	14	constructs	construct	NOUN
flr-135	54	15	derived	derive	VERB
flr-135	54	16	from	from	ADP
flr-135	54	17	previous	previous	ADJ
flr-135	54	18	cognitive	cognitive	ADJ
flr-135	54	19	,	,	PUNCT
flr-135	54	20	motivational	motivational	NOUN
flr-135	54	21	,	,	PUNCT
flr-135	54	22	and	and	CCONJ
flr-135	54	23	sociodemographic	sociodemographic	ADJ
flr-135	54	24	research	research	NOUN
flr-135	54	25	and	and	CCONJ
flr-135	54	26	models	model	NOUN
flr-135	54	27	,	,	PUNCT
flr-135	54	28	avoiding	avoid	VERB
flr-135	54	29	blind	blind	ADJ
flr-135	54	30	data	datum	NOUN
flr-135	54	31	mining	mining	NOUN
flr-135	54	32	techniques	technique	NOUN
flr-135	54	33	(	(	PUNCT
flr-135	54	34	hand	hand	NOUN
flr-135	54	35	,	,	PUNCT
flr-135	54	36	mannila	mannila	PROPN
flr-135	54	37	&	&	CCONJ
flr-135	54	38	smyth	smyth	PROPN
flr-135	54	39	,	,	PUNCT
flr-135	54	40	2001	2001	NUM
flr-135	54	41	)	)	PUNCT
flr-135	54	42	,	,	PUNCT
flr-135	54	43	and	and	CCONJ
flr-135	54	44	based	base	VERB
flr-135	54	45	on	on	ADP
flr-135	54	46	the	the	DET
flr-135	54	47	factor	factor	NOUN
flr-135	54	48	analysis	analysis	NOUN
flr-135	54	49	and	and	CCONJ
flr-135	54	50	structural	structural	ADJ
flr-135	54	51	equation	equation	NOUN
flr-135	54	52	modelling	modelling	NOUN
flr-135	54	53	(	(	PUNCT
flr-135	54	54	sem	sem	NOUN
flr-135	54	55	)	)	PUNCT
flr-135	54	56	of	of	ADP
flr-135	54	57	several	several	ADJ
flr-135	54	58	variables	variable	NOUN
flr-135	54	59	to	to	PART
flr-135	54	60	determine	determine	VERB
flr-135	54	61	their	their	PRON
flr-135	54	62	potential	potential	ADJ
flr-135	54	63	weight	weight	NOUN
flr-135	54	64	in	in	ADP
flr-135	54	65	the	the	DET
flr-135	54	66	problem	problem	NOUN
flr-135	54	67	.	.	PUNCT
flr-135	55	1	cause	cause	VERB
flr-135	55	2	-	-	PUNCT
flr-135	55	3	and	and	CCONJ
flr-135	55	4	-	-	PUNCT
flr-135	55	5	effect	effect	NOUN
flr-135	55	6	relationships	relationship	NOUN
flr-135	55	7	have	have	AUX
flr-135	55	8	been	be	AUX
flr-135	55	9	traditionally	traditionally	ADV
flr-135	55	10	modelled	model	VERB
flr-135	55	11	,	,	PUNCT
flr-135	55	12	among	among	ADP
flr-135	55	13	others	other	NOUN
flr-135	55	14	,	,	PUNCT
flr-135	55	15	by	by	ADP
flr-135	55	16	sem	sem	NOUN
flr-135	55	17	and	and	CCONJ
flr-135	55	18	partial	partial	ADJ
flr-135	55	19	least	least	ADJ
flr-135	55	20	squares	square	NOUN
flr-135	55	21	(	(	PUNCT
flr-135	55	22	pls	pls	INTJ
flr-135	55	23	)	)	PUNCT
flr-135	55	24	approaches	approach	NOUN
flr-135	55	25	.	.	PUNCT
flr-135	56	1	but	but	CCONJ
flr-135	56	2	these	these	DET
flr-135	56	3	procedures	procedure	NOUN
flr-135	56	4	have	have	VERB
flr-135	56	5	their	their	PRON
flr-135	56	6	own	own	ADJ
flr-135	56	7	shortcomings	shortcoming	NOUN
flr-135	56	8	.	.	PUNCT
flr-135	57	1	in	in	ADP
flr-135	57	2	pls	pls	INTJ
flr-135	57	3	,	,	PUNCT
flr-135	57	4	there	there	PRON
flr-135	57	5	is	be	VERB
flr-135	57	6	no	no	DET
flr-135	57	7	theoretical	theoretical	ADJ
flr-135	57	8	rationale	rationale	NOUN
flr-135	57	9	for	for	ADP
flr-135	57	10	all	all	DET
flr-135	57	11	indicators	indicator	NOUN
flr-135	57	12	to	to	PART
flr-135	57	13	have	have	VERB
flr-135	57	14	the	the	DET
flr-135	57	15	same	same	ADJ
flr-135	57	16	weighting	weighting	NOUN
flr-135	57	17	(	(	PUNCT
flr-135	57	18	haenlein	haenlein	PROPN
flr-135	57	19	&	&	CCONJ
flr-135	57	20	kaplan	kaplan	PROPN
flr-135	57	21	,	,	PUNCT
flr-135	57	22	2004	2004	NUM
flr-135	57	23	)	)	PUNCT
flr-135	57	24	,	,	PUNCT
flr-135	57	25	and	and	CCONJ
flr-135	57	26	the	the	DET
flr-135	57	27	pls	pls	NOUN
flr-135	57	28	procedure	procedure	NOUN
flr-135	57	29	does	do	AUX
flr-135	57	30	not	not	PART
flr-135	57	31	take	take	VERB
flr-135	57	32	into	into	ADP
flr-135	57	33	account	account	NOUN
flr-135	57	34	the	the	DET
flr-135	57	35	fact	fact	NOUN
flr-135	57	36	that	that	SCONJ
flr-135	57	37	some	some	DET
flr-135	57	38	indicators	indicator	NOUN
flr-135	57	39	may	may	AUX
flr-135	57	40	be	be	AUX
flr-135	57	41	more	more	ADV
flr-135	57	42	reliable	reliable	ADJ
flr-135	57	43	than	than	ADP
flr-135	57	44	others	other	NOUN
flr-135	57	45	and	and	CCONJ
flr-135	57	46	should	should	AUX
flr-135	57	47	,	,	PUNCT
flr-135	57	48	therefore	therefore	ADV
flr-135	57	49	,	,	PUNCT
flr-135	57	50	receive	receive	VERB
flr-135	57	51	higher	high	ADJ
flr-135	57	52	weights	weight	NOUN
flr-135	57	53	(	(	PUNCT
flr-135	57	54	chin	chin	NOUN
flr-135	57	55	,	,	PUNCT
flr-135	57	56	marcolin	marcolin	NOUN
flr-135	57	57	,	,	PUNCT
flr-135	57	58	&	&	CCONJ
flr-135	57	59	newsted	newste	VERB
flr-135	57	60	(	(	PUNCT
flr-135	57	61	2003	2003	NUM
flr-135	57	62	)	)	PUNCT
flr-135	57	63	.	.	PUNCT
flr-135	58	1	in	in	ADP
flr-135	58	2	addition	addition	NOUN
flr-135	58	3	,	,	PUNCT
flr-135	58	4	there	there	PRON
flr-135	58	5	is	be	VERB
flr-135	58	6	the	the	DET
flr-135	58	7	difficulty	difficulty	NOUN
flr-135	58	8	of	of	ADP
flr-135	58	9	interpreting	interpret	VERB
flr-135	58	10	the	the	DET
flr-135	58	11	loadings	loading	NOUN
flr-135	58	12	of	of	ADP
flr-135	58	13	the	the	DET
flr-135	58	14	independent	independent	ADJ
flr-135	58	15	latent	latent	NOUN
flr-135	58	16	variables	variable	NOUN
flr-135	58	17	in	in	ADP
flr-135	58	18	pls	pls	PROPN
flr-135	58	19	(	(	PUNCT
flr-135	58	20	which	which	PRON
flr-135	58	21	are	be	AUX
flr-135	58	22	based	base	VERB
flr-135	58	23	on	on	ADP
flr-135	58	24	cross	cross	ADJ
flr-135	58	25	-	-	ADJ
flr-135	58	26	product	product	ADJ
flr-135	58	27	relations	relation	NOUN
flr-135	58	28	with	with	ADP
flr-135	58	29	the	the	DET
flr-135	58	30	response	response	NOUN
flr-135	58	31	variables	variable	NOUN
flr-135	58	32	)	)	PUNCT
flr-135	58	33	.	.	PUNCT
flr-135	59	1	regarding	regard	VERB
flr-135	59	2	sem	sem	NOUN
flr-135	59	3	several	several	ADJ
flr-135	59	4	authors	author	NOUN
flr-135	59	5	also	also	ADV
flr-135	59	6	point	point	VERB
flr-135	59	7	out	out	ADP
flr-135	59	8	some	some	DET
flr-135	59	9	issues	issue	NOUN
flr-135	59	10	that	that	PRON
flr-135	59	11	require	require	VERB
flr-135	59	12	attention	attention	NOUN
flr-135	59	13	from	from	ADP
flr-135	59	14	the	the	DET
flr-135	59	15	researcher	researcher	NOUN
flr-135	59	16	or	or	CCONJ
flr-135	59	17	that	that	PRON
flr-135	59	18	are	be	AUX
flr-135	59	19	still	still	ADV
flr-135	59	20	awaiting	await	VERB
flr-135	59	21	further	further	ADJ
flr-135	59	22	research	research	NOUN
flr-135	59	23	(	(	PUNCT
flr-135	59	24	lei	lei	PROPN
flr-135	59	25	&	&	CCONJ
flr-135	59	26	qiong	qiong	PROPN
flr-135	59	27	wu	wu	PROPN
flr-135	59	28	,	,	PUNCT
flr-135	59	29	2007	2007	NUM
flr-135	59	30	;	;	PUNCT
flr-135	59	31	schermelleh	schermelleh	NOUN
flr-135	59	32	-	-	PUNCT
flr-135	59	33	engel	engel	PROPN
flr-135	59	34	,	,	PUNCT
flr-135	59	35	kerwer	kerwer	PROPN
flr-135	59	36	,	,	PUNCT
flr-135	59	37	&	&	CCONJ
flr-135	59	38	klein	klein	PROPN
flr-135	59	39	,	,	PUNCT
flr-135	59	40	2014	2014	NUM
flr-135	59	41	;	;	PUNCT
flr-135	59	42	weston	weston	PROPN
flr-135	59	43	&	&	CCONJ
flr-135	59	44	gore	gore	PROPN
flr-135	59	45	,	,	PUNCT
flr-135	59	46	2006	2006	NUM
flr-135	59	47	)	)	PUNCT
flr-135	59	48	.	.	PUNCT
flr-135	60	1	among	among	ADP
flr-135	60	2	the	the	DET
flr-135	60	3	issues	issue	NOUN
flr-135	60	4	noted	note	VERB
flr-135	60	5	with	with	ADP
flr-135	60	6	sem	sem	PROPN
flr-135	60	7	are	be	AUX
flr-135	60	8	possible	possible	ADJ
flr-135	60	9	data	datum	NOUN
flr-135	60	10	problems	problem	NOUN
flr-135	60	11	,	,	PUNCT
flr-135	60	12	such	such	ADJ
flr-135	60	13	as	as	ADP
flr-135	60	14	missing	miss	VERB
flr-135	60	15	data	datum	NOUN
flr-135	60	16	,	,	PUNCT
flr-135	60	17	non	non	ADJ
flr-135	60	18	-	-	NOUN
flr-135	60	19	normality	normality	NOUN
flr-135	60	20	of	of	ADP
flr-135	60	21	observed	observed	ADJ
flr-135	60	22	variables	variable	NOUN
flr-135	60	23	,	,	PUNCT
flr-135	60	24	or	or	CCONJ
flr-135	60	25	multicollinearity	multicollinearity	NOUN
flr-135	60	26	;	;	PUNCT
flr-135	60	27	estimation	estimation	NOUN
flr-135	60	28	problems	problem	NOUN
flr-135	60	29	that	that	PRON
flr-135	60	30	could	could	AUX
flr-135	60	31	be	be	AUX
flr-135	60	32	due	due	ADJ
flr-135	60	33	to	to	ADP
flr-135	60	34	data	datum	NOUN
flr-135	60	35	problems	problem	NOUN
flr-135	60	36	or	or	CCONJ
flr-135	60	37	identification	identification	NOUN
flr-135	60	38	problems	problem	NOUN
flr-135	60	39	in	in	ADP
flr-135	60	40	model	model	NOUN
flr-135	60	41	specification	specification	NOUN
flr-135	60	42	;	;	PUNCT
flr-135	60	43	or	or	CCONJ
flr-135	60	44	interpretation	interpretation	NOUN
flr-135	60	45	problems	problem	NOUN
flr-135	60	46	due	due	ADJ
flr-135	60	47	to	to	ADP
flr-135	60	48	unreasonable	unreasonable	ADJ
flr-135	60	49	estimates	estimate	NOUN
flr-135	60	50	.	.	PUNCT
flr-135	61	1	these	these	DET
flr-135	61	2	potential	potential	ADJ
flr-135	61	3	problems	problem	NOUN
flr-135	61	4	have	have	AUX
flr-135	61	5	led	lead	VERB
flr-135	61	6	to	to	ADP
flr-135	61	7	suggestions	suggestion	NOUN
flr-135	61	8	involving	involve	VERB
flr-135	61	9	the	the	DET
flr-135	61	10	development	development	NOUN
flr-135	61	11	of	of	ADP
flr-135	61	12	“	"	PUNCT
flr-135	61	13	mixture	mixture	NOUN
flr-135	61	14	pls	pls	NOUN
flr-135	61	15	”	"	PUNCT
flr-135	61	16	models	model	NOUN
flr-135	61	17	(	(	PUNCT
flr-135	61	18	hahn	hahn	PROPN
flr-135	61	19	,	,	PUNCT
flr-135	61	20	johnson	johnson	PROPN
flr-135	61	21	,	,	PUNCT
flr-135	61	22	herrmann	herrmann	PROPN
flr-135	61	23	,	,	PUNCT
flr-135	61	24	&	&	CCONJ
flr-135	61	25	huber	huber	PROPN
flr-135	61	26	,	,	PUNCT
flr-135	61	27	2002	2002	NUM
flr-135	61	28	)	)	PUNCT
flr-135	61	29	,	,	PUNCT
flr-135	61	30	hierarchical	hierarchical	ADJ
flr-135	61	31	bayesian	bayesian	NOUN
flr-135	61	32	methods	method	NOUN
flr-135	61	33	in	in	ADP
flr-135	61	34	sem	sem	NOUN
flr-135	61	35	models	model	NOUN
flr-135	61	36	(	(	PUNCT
flr-135	61	37	ansari	ansari	X
flr-135	61	38	,	,	PUNCT
flr-135	61	39	jedidi	jedidi	PROPN
flr-135	61	40	,	,	PUNCT
flr-135	61	41	&	&	CCONJ
flr-135	61	42	jagpal	jagpal	PROPN
flr-135	61	43	,	,	PUNCT
flr-135	61	44	2000	2000	NUM
flr-135	61	45	)	)	PUNCT
flr-135	61	46	and	and	CCONJ
flr-135	61	47	new	new	ADJ
flr-135	61	48	ways	way	NOUN
flr-135	61	49	of	of	ADP
flr-135	61	50	evaluating	evaluate	VERB
flr-135	61	51	fit	fit	NOUN
flr-135	61	52	in	in	ADP
flr-135	61	53	non	non	ADJ
flr-135	61	54	-	-	ADJ
flr-135	61	55	linear	linear	ADJ
flr-135	61	56	multilevel	multilevel	ADJ
flr-135	61	57	structural	structural	ADJ
flr-135	61	58	equation	equation	NOUN
flr-135	61	59	models	model	NOUN
flr-135	61	60	(	(	PUNCT
flr-135	61	61	schermelleh	schermelleh	NOUN
flr-135	61	62	-	-	PUNCT
flr-135	61	63	engel	engel	PROPN
flr-135	61	64	et	et	PROPN
flr-135	61	65	al	al	PROPN
flr-135	61	66	.	.	PROPN
flr-135	61	67	,	,	PUNCT
flr-135	61	68	2014	2014	NUM
flr-135	61	69	)	)	PUNCT
flr-135	61	70	.	.	PUNCT
flr-135	62	1	even	even	ADV
flr-135	62	2	if	if	SCONJ
flr-135	62	3	nonlinear	nonlinear	ADJ
flr-135	62	4	sem	sem	NOUN
flr-135	62	5	and	and	CCONJ
flr-135	62	6	pls	pls	PROPN
flr-135	62	7	models	model	NOUN
flr-135	62	8	could	could	AUX
flr-135	62	9	handle	handle	VERB
flr-135	62	10	asymmetric	asymmetric	ADJ
flr-135	62	11	relationships	relationship	NOUN
flr-135	62	12	,	,	PUNCT
flr-135	62	13	they	they	PRON
flr-135	62	14	still	still	ADV
flr-135	62	15	do	do	AUX
flr-135	62	16	not	not	PART
flr-135	62	17	solve	solve	VERB
flr-135	62	18	the	the	DET
flr-135	62	19	problems	problem	NOUN
flr-135	62	20	associated	associate	VERB
flr-135	62	21	with	with	ADP
flr-135	62	22	large	large	ADJ
flr-135	62	23	data	datum	NOUN
flr-135	62	24	and	and	CCONJ
flr-135	62	25	complex	complex	ADJ
flr-135	62	26	interactions	interaction	NOUN
flr-135	62	27	.	.	PUNCT
flr-135	63	1	the	the	DET
flr-135	63	2	snn	snn	PROPN
flr-135	63	3	approach	approach	NOUN
flr-135	63	4	takes	take	VERB
flr-135	63	5	into	into	ADP
flr-135	63	6	account	account	NOUN
flr-135	63	7	these	these	DET
flr-135	63	8	complexities	complexity	NOUN
flr-135	63	9	and	and	CCONJ
flr-135	63	10	non	non	ADJ
flr-135	63	11	-	-	NOUN
flr-135	63	12	linearity	linearity	NOUN
flr-135	63	13	in	in	ADP
flr-135	63	14	data	datum	NOUN
flr-135	63	15	sets	set	NOUN
flr-135	63	16	,	,	PUNCT
flr-135	63	17	while	while	SCONJ
flr-135	63	18	maintaining	maintain	VERB
flr-135	63	19	the	the	DET
flr-135	63	20	advantages	advantage	NOUN
flr-135	63	21	of	of	ADP
flr-135	63	22	the	the	DET
flr-135	63	23	ann	ann	PROPN
flr-135	63	24	general	general	PROPN
flr-135	63	25	model	model	PROPN
flr-135	63	26	.	.	PUNCT
flr-135	64	1	another	another	DET
flr-135	64	2	significant	significant	ADJ
flr-135	64	3	addition	addition	NOUN
flr-135	64	4	to	to	ADP
flr-135	64	5	the	the	DET
flr-135	64	6	battery	battery	NOUN
flr-135	64	7	of	of	ADP
flr-135	64	8	approaches	approach	NOUN
flr-135	64	9	that	that	PRON
flr-135	64	10	researchers	researcher	NOUN
flr-135	64	11	have	have	AUX
flr-135	64	12	explored	explore	VERB
flr-135	64	13	to	to	PART
flr-135	64	14	eliminate	eliminate	VERB
flr-135	64	15	the	the	DET
flr-135	64	16	“	"	PUNCT
flr-135	64	17	black	black	ADJ
flr-135	64	18	box	box	NOUN
flr-135	64	19	”	"	PUNCT
flr-135	64	20	risk	risk	NOUN
flr-135	64	21	of	of	ADP
flr-135	64	22	anns	anns	NOUN
flr-135	64	23	is	be	AUX
flr-135	64	24	the	the	DET
flr-135	64	25	inclusion	inclusion	NOUN
flr-135	64	26	of	of	ADP
flr-135	64	27	sensitivity	sensitivity	NOUN
flr-135	64	28	analysis	analysis	NOUN
flr-135	64	29	for	for	ADP
flr-135	64	30	each	each	PRON
flr-135	64	31	of	of	ADP
flr-135	64	32	the	the	DET
flr-135	64	33	variables	variable	NOUN
flr-135	64	34	in	in	ADP
flr-135	64	35	the	the	DET
flr-135	64	36	model	model	NOUN
flr-135	64	37	(	(	PUNCT
flr-135	64	38	kim	kim	PROPN
flr-135	64	39	&	&	CCONJ
flr-135	64	40	ahn	ahn	PROPN
flr-135	64	41	,	,	PUNCT
flr-135	64	42	2009	2009	NUM
flr-135	64	43	)	)	PUNCT
flr-135	64	44	in	in	ADP
flr-135	64	45	order	order	NOUN
flr-135	64	46	to	to	PART
flr-135	64	47	extract	extract	VERB
flr-135	64	48	the	the	DET
flr-135	64	49	necessary	necessary	ADJ
flr-135	64	50	information	information	NOUN
flr-135	64	51	for	for	ADP
flr-135	64	52	model	model	NOUN
flr-135	64	53	validation	validation	NOUN
flr-135	64	54	and	and	CCONJ
flr-135	64	55	process	process	NOUN
flr-135	64	56	optimisation	optimisation	NOUN
flr-135	64	57	,	,	PUNCT
flr-135	64	58	from	from	ADP
flr-135	64	59	the	the	DET
flr-135	64	60	relationships	relationship	NOUN
flr-135	64	61	between	between	ADP
flr-135	64	62	inputs	input	NOUN
flr-135	64	63	and	and	CCONJ
flr-135	64	64	outputs	output	NOUN
flr-135	64	65	in	in	ADP
flr-135	64	66	the	the	DET
flr-135	64	67	ann	ann	PROPN
flr-135	64	68	.	.	PUNCT
flr-135	65	1	this	this	DET
flr-135	65	2	method	method	NOUN
flr-135	65	3	,	,	PUNCT
flr-135	65	4	based	base	VERB
flr-135	65	5	on	on	ADP
flr-135	65	6	the	the	DET
flr-135	65	7	relative	relative	ADJ
flr-135	65	8	importance	importance	NOUN
flr-135	65	9	(	(	PUNCT
flr-135	65	10	ri	ri	NOUN
flr-135	65	11	)	)	PUNCT
flr-135	65	12	parameter	parameter	NOUN
flr-135	65	13	estimate	estimate	NOUN
flr-135	65	14	improves	improve	VERB
flr-135	65	15	on	on	ADP
flr-135	65	16	garson‟s	garson‟s	X
flr-135	65	17	(	(	PUNCT
flr-135	65	18	1991	1991	NUM
flr-135	65	19	)	)	PUNCT
flr-135	65	20	use	use	NOUN
flr-135	65	21	of	of	ADP
flr-135	65	22	relative	relative	ADJ
flr-135	65	23	importance	importance	NOUN
flr-135	65	24	weights	weight	NOUN
flr-135	65	25	,	,	PUNCT
flr-135	65	26	and	and	CCONJ
flr-135	65	27	uses	use	VERB
flr-135	65	28	sensitivity	sensitivity	NOUN
flr-135	65	29	analysis	analysis	NOUN
flr-135	65	30	to	to	PART
flr-135	65	31	determine	determine	VERB
flr-135	65	32	the	the	DET
flr-135	65	33	causal	causal	ADJ
flr-135	65	34	importance	importance	NOUN
flr-135	65	35	of	of	ADP
flr-135	65	36	the	the	DET
flr-135	65	37	input	input	NOUN
flr-135	65	38	variables	variable	VERB
flr-135	65	39	on	on	ADP
flr-135	65	40	the	the	DET
flr-135	65	41	outputs	output	NOUN
flr-135	65	42	.	.	PUNCT
flr-135	66	1	the	the	DET
flr-135	66	2	sensitivity	sensitivity	NOUN
flr-135	66	3	is	be	AUX
flr-135	66	4	a	a	DET
flr-135	66	5	measure	measure	NOUN
flr-135	66	6	of	of	ADP
flr-135	66	7	the	the	DET
flr-135	66	8	increase	increase	NOUN
flr-135	66	9	in	in	ADP
flr-135	66	10	the	the	DET
flr-135	66	11	error	error	NOUN
flr-135	66	12	of	of	ADP
flr-135	66	13	the	the	DET
flr-135	66	14	predicted	predict	VERB
flr-135	66	15	value	value	NOUN
flr-135	66	16	as	as	SCONJ
flr-135	66	17	each	each	DET
flr-135	66	18	variable	variable	NOUN
flr-135	66	19	is	be	AUX
flr-135	66	20	excluded	exclude	VERB
flr-135	66	21	from	from	ADP
flr-135	66	22	the	the	DET
flr-135	66	23	model	model	NOUN
flr-135	66	24	,	,	PUNCT
flr-135	66	25	and	and	CCONJ
flr-135	66	26	demonstrates	demonstrate	VERB
flr-135	66	27	systematically	systematically	ADV
flr-135	66	28	the	the	DET
flr-135	66	29	degree	degree	NOUN
flr-135	66	30	of	of	ADP
flr-135	66	31	influence	influence	NOUN
flr-135	66	32	on	on	ADP
flr-135	66	33	the	the	DET
flr-135	66	34	network	network	NOUN
flr-135	66	35	weights	weight	NOUN
flr-135	66	36	of	of	ADP
flr-135	66	37	each	each	DET
flr-135	66	38	participating	participate	VERB
flr-135	66	39	variable	variable	NOUN
flr-135	66	40	.	.	PUNCT
flr-135	67	1	the	the	DET
flr-135	67	2	ri	ri	PROPN
flr-135	67	3	methods	method	NOUN
flr-135	67	4	used	use	VERB
flr-135	67	5	in	in	ADP
flr-135	67	6	both	both	CCONJ
flr-135	67	7	classification	classification	NOUN
flr-135	67	8	and	and	CCONJ
flr-135	67	9	prediction	prediction	NOUN
flr-135	67	10	models	model	NOUN
flr-135	67	11	are	be	AUX
flr-135	67	12	another	another	DET
flr-135	67	13	evidence	evidence	NOUN
flr-135	67	14	of	of	ADP
flr-135	67	15	the	the	DET
flr-135	67	16	fallacy	fallacy	NOUN
flr-135	67	17	of	of	ADP
flr-135	67	18	the	the	DET
flr-135	67	19	https://www.researchgate.net/researcher/2045138797_karin_schermelleh-engel/	https://www.researchgate.net/researcher/2045138797_karin_schermelleh-engel/	PROPN
flr-135	67	20	https://www.researchgate.net/researcher/2045138797_karin_schermelleh-engel/	https://www.researchgate.net/researcher/2045138797_karin_schermelleh-engel/	PROPN
flr-135	67	21	cascallar	cascallar	NOUN
flr-135	67	22	et	et	NOUN
flr-135	67	23	al	al	PROPN
flr-135	67	24	71	71	NUM
flr-135	68	1	|	|	CCONJ
flr-135	68	2	f	f	NOUN
flr-135	68	3	l	l	NOUN
flr-135	68	4	r	r	NOUN
flr-135	68	5	view	view	NOUN
flr-135	68	6	of	of	ADP
flr-135	68	7	neural	neural	ADJ
flr-135	68	8	networks	network	NOUN
flr-135	68	9	as	as	ADP
flr-135	68	10	black	black	ADJ
flr-135	68	11	-	-	PUNCT
flr-135	68	12	boxes	box	NOUN
flr-135	68	13	beyond	beyond	ADP
flr-135	68	14	human	human	ADJ
flr-135	68	15	understanding	understanding	NOUN
flr-135	68	16	.	.	PUNCT
flr-135	69	1	incidentally	incidentally	ADV
flr-135	69	2	,	,	PUNCT
flr-135	69	3	kim	kim	PROPN
flr-135	69	4	and	and	CCONJ
flr-135	69	5	ahn	ahn	PROPN
flr-135	69	6	(	(	PUNCT
flr-135	69	7	2009	2009	NUM
flr-135	69	8	)	)	PUNCT
flr-135	69	9	also	also	ADV
flr-135	69	10	compared	compare	VERB
flr-135	69	11	the	the	DET
flr-135	69	12	results	result	NOUN
flr-135	69	13	from	from	ADP
flr-135	69	14	the	the	DET
flr-135	69	15	ann	ann	PROPN
flr-135	69	16	analysis	analysis	NOUN
flr-135	69	17	with	with	ADP
flr-135	69	18	logistic	logistic	ADJ
flr-135	69	19	regression	regression	NOUN
flr-135	69	20	and	and	CCONJ
flr-135	69	21	classification	classification	NOUN
flr-135	69	22	and	and	CCONJ
flr-135	69	23	regression	regression	NOUN
flr-135	69	24	trees	tree	NOUN
flr-135	69	25	(	(	PUNCT
flr-135	69	26	cart	cart	NOUN
flr-135	69	27	)	)	PUNCT
flr-135	69	28	analyses	analysis	NOUN
flr-135	69	29	,	,	PUNCT
flr-135	69	30	with	with	ADP
flr-135	69	31	ann	ann	PROPN
flr-135	69	32	models	model	NOUN
flr-135	69	33	obtaining	obtain	VERB
flr-135	69	34	better	well	ADJ
flr-135	69	35	results	result	NOUN
flr-135	69	36	in	in	ADP
flr-135	69	37	both	both	DET
flr-135	69	38	training	training	NOUN
flr-135	69	39	and	and	CCONJ
flr-135	69	40	testing	testing	NOUN
flr-135	69	41	sets	set	NOUN
flr-135	69	42	of	of	ADP
flr-135	69	43	data	datum	NOUN
flr-135	69	44	.	.	PUNCT
flr-135	70	1	other	other	ADJ
flr-135	70	2	authors	author	NOUN
flr-135	70	3	(	(	PUNCT
flr-135	70	4	e.g.	e.g.	ADV
flr-135	70	5	,	,	PUNCT
flr-135	70	6	blackard	blackard	PROPN
flr-135	70	7	&	&	CCONJ
flr-135	70	8	dean	dean	PROPN
flr-135	70	9	,	,	PUNCT
flr-135	70	10	1999	1999	NUM
flr-135	70	11	)	)	PUNCT
flr-135	70	12	have	have	AUX
flr-135	70	13	compared	compare	VERB
flr-135	70	14	anns	anns	ADJ
flr-135	70	15	absolute	absolute	ADJ
flr-135	70	16	accuracy	accuracy	NOUN
flr-135	70	17	and	and	CCONJ
flr-135	70	18	relative	relative	ADJ
flr-135	70	19	accuracy	accuracy	NOUN
flr-135	70	20	compared	compare	VERB
flr-135	70	21	to	to	ADP
flr-135	70	22	predictions	prediction	NOUN
flr-135	70	23	based	base	VERB
flr-135	70	24	on	on	ADP
flr-135	70	25	discriminant	discriminant	ADJ
flr-135	70	26	analysis	analysis	NOUN
flr-135	70	27	(	(	PUNCT
flr-135	70	28	da	da	NOUN
flr-135	70	29	)	)	PUNCT
flr-135	70	30	models	model	NOUN
flr-135	70	31	,	,	PUNCT
flr-135	70	32	with	with	ADP
flr-135	70	33	a	a	DET
flr-135	70	34	consistent	consistent	ADJ
flr-135	70	35	finding	finding	NOUN
flr-135	70	36	that	that	SCONJ
flr-135	70	37	ann	ann	PROPN
flr-135	70	38	models	model	NOUN
flr-135	70	39	outperformed	outperform	VERB
flr-135	70	40	the	the	DET
flr-135	70	41	da	da	PROPN
flr-135	70	42	models	model	NOUN
flr-135	70	43	.	.	PUNCT
flr-135	71	1	a	a	DET
flr-135	71	2	very	very	ADV
flr-135	71	3	interesting	interesting	ADJ
flr-135	71	4	comparison	comparison	NOUN
flr-135	71	5	of	of	ADP
flr-135	71	6	methods	method	NOUN
flr-135	71	7	to	to	PART
flr-135	71	8	accurately	accurately	ADV
flr-135	71	9	assess	assess	VERB
flr-135	71	10	the	the	DET
flr-135	71	11	contribution	contribution	NOUN
flr-135	71	12	of	of	ADP
flr-135	71	13	variables	variable	NOUN
flr-135	71	14	in	in	ADP
flr-135	71	15	ann	ann	PROPN
flr-135	71	16	architectures	architecture	NOUN
flr-135	71	17	has	have	AUX
flr-135	71	18	been	be	AUX
flr-135	71	19	reported	report	VERB
flr-135	71	20	by	by	ADP
flr-135	71	21	olden	olden	ADJ
flr-135	71	22	,	,	PUNCT
flr-135	71	23	joy	joy	NOUN
flr-135	71	24	,	,	PUNCT
flr-135	71	25	and	and	CCONJ
flr-135	71	26	death	death	NOUN
flr-135	71	27	(	(	PUNCT
flr-135	71	28	2004	2004	NUM
flr-135	71	29	)	)	PUNCT
flr-135	71	30	.	.	PUNCT
flr-135	72	1	the	the	DET
flr-135	72	2	authors	author	NOUN
flr-135	72	3	compare	compare	VERB
flr-135	72	4	nine	nine	NUM
flr-135	72	5	different	different	ADJ
flr-135	72	6	methods	method	NOUN
flr-135	72	7	for	for	ADP
flr-135	72	8	quantifying	quantify	VERB
flr-135	72	9	variable	variable	ADJ
flr-135	72	10	importance	importance	NOUN
flr-135	72	11	in	in	ADP
flr-135	72	12	anns	anns	NOUN
flr-135	72	13	using	use	VERB
flr-135	72	14	simulated	simulated	ADJ
flr-135	72	15	data	datum	NOUN
flr-135	72	16	with	with	ADP
flr-135	72	17	known	know	VERB
flr-135	72	18	properties	property	NOUN
flr-135	72	19	.	.	PUNCT
flr-135	73	1	the	the	DET
flr-135	73	2	use	use	NOUN
flr-135	73	3	of	of	ADP
flr-135	73	4	simulated	simulated	ADJ
flr-135	73	5	data	datum	NOUN
flr-135	73	6	,	,	PUNCT
flr-135	73	7	when	when	SCONJ
flr-135	73	8	the	the	DET
flr-135	73	9	true	true	ADJ
flr-135	73	10	importance	importance	NOUN
flr-135	73	11	of	of	ADP
flr-135	73	12	the	the	DET
flr-135	73	13	variables	variable	NOUN
flr-135	73	14	is	be	AUX
flr-135	73	15	known	know	VERB
flr-135	73	16	,	,	PUNCT
flr-135	73	17	provides	provide	VERB
flr-135	73	18	a	a	DET
flr-135	73	19	solid	solid	ADJ
flr-135	73	20	base	base	NOUN
flr-135	73	21	for	for	ADP
flr-135	73	22	future	future	ADJ
flr-135	73	23	developments	development	NOUN
flr-135	73	24	in	in	ADP
flr-135	73	25	this	this	DET
flr-135	73	26	field	field	NOUN
flr-135	73	27	,	,	PUNCT
flr-135	73	28	which	which	PRON
flr-135	73	29	are	be	AUX
flr-135	73	30	not	not	PART
flr-135	73	31	possible	possible	ADJ
flr-135	73	32	with	with	ADP
flr-135	73	33	natural	natural	ADJ
flr-135	73	34	data	datum	NOUN
flr-135	73	35	as	as	SCONJ
flr-135	73	36	is	be	AUX
flr-135	73	37	the	the	DET
flr-135	73	38	case	case	NOUN
flr-135	73	39	with	with	ADP
flr-135	73	40	gevrey	gevrey	PROPN
flr-135	73	41	,	,	PUNCT
flr-135	73	42	dimopoulos	dimopoulo	NOUN
flr-135	73	43	,	,	PUNCT
flr-135	73	44	and	and	CCONJ
flr-135	73	45	lek	lek	PROPN
flr-135	73	46	(	(	PUNCT
flr-135	73	47	2003	2003	NUM
flr-135	73	48	)	)	PUNCT
flr-135	73	49	.	.	PUNCT
flr-135	74	1	the	the	DET
flr-135	74	2	nine	nine	NUM
flr-135	74	3	methodologies	methodology	NOUN
flr-135	74	4	studied	study	VERB
flr-135	74	5	by	by	ADP
flr-135	74	6	olden	olden	PROPN
flr-135	74	7	et	et	PROPN
flr-135	74	8	al	al	PROPN
flr-135	74	9	.	.	PROPN
flr-135	74	10	(	(	PUNCT
flr-135	74	11	2004	2004	NUM
flr-135	74	12	)	)	PUNCT
flr-135	74	13	included	include	VERB
flr-135	74	14	:	:	PUNCT
flr-135	74	15	connection	connection	NOUN
flr-135	74	16	weights	weight	NOUN
flr-135	74	17	,	,	PUNCT
flr-135	74	18	garson‟s	garson‟s	NOUN
flr-135	74	19	algorithm	algorithm	NOUN
flr-135	74	20	,	,	PUNCT
flr-135	74	21	partial	partial	ADJ
flr-135	74	22	derivatives	derivative	NOUN
flr-135	74	23	,	,	PUNCT
flr-135	74	24	input	input	NOUN
flr-135	74	25	perturbation	perturbation	NOUN
flr-135	74	26	,	,	PUNCT
flr-135	74	27	sensitivity	sensitivity	NOUN
flr-135	74	28	analysis	analysis	NOUN
flr-135	74	29	,	,	PUNCT
flr-135	74	30	forward	forward	ADV
flr-135	74	31	stepwise	stepwise	PROPN
flr-135	74	32	addition	addition	NOUN
flr-135	74	33	,	,	PUNCT
flr-135	74	34	backward	backward	ADJ
flr-135	74	35	stepwise	stepwise	PROPN
flr-135	74	36	elimination	elimination	NOUN
flr-135	74	37	,	,	PUNCT
flr-135	74	38	improved	improve	VERB
flr-135	74	39	stepwise	stepwise	ADJ
flr-135	74	40	selection	selection	NOUN
flr-135	74	41	1	1	NUM
flr-135	74	42	,	,	PUNCT
flr-135	74	43	and	and	CCONJ
flr-135	74	44	improved	improve	VERB
flr-135	74	45	stepwise	stepwise	ADJ
flr-135	74	46	selection	selection	NOUN
flr-135	74	47	2	2	NUM
flr-135	74	48	(	(	PUNCT
flr-135	74	49	see	see	VERB
flr-135	74	50	olden	olden	ADJ
flr-135	74	51	et	et	PROPN
flr-135	74	52	al	al	PROPN
flr-135	74	53	.	.	PROPN
flr-135	74	54	,	,	PUNCT
flr-135	74	55	2004	2004	NUM
flr-135	74	56	for	for	ADP
flr-135	74	57	details	detail	NOUN
flr-135	74	58	on	on	ADP
flr-135	74	59	these	these	DET
flr-135	74	60	methods	method	NOUN
flr-135	74	61	)	)	PUNCT
flr-135	74	62	.	.	PUNCT
flr-135	75	1	the	the	DET
flr-135	75	2	results	result	NOUN
flr-135	75	3	indicated	indicate	VERB
flr-135	75	4	that	that	SCONJ
flr-135	75	5	the	the	DET
flr-135	75	6	connection	connection	NOUN
flr-135	75	7	weights	weight	NOUN
flr-135	75	8	approach	approach	NOUN
flr-135	75	9	showed	show	VERB
flr-135	75	10	the	the	DET
flr-135	75	11	best	good	ADJ
flr-135	75	12	overall	overall	ADJ
flr-135	75	13	performance	performance	NOUN
flr-135	75	14	both	both	CCONJ
flr-135	75	15	in	in	ADP
flr-135	75	16	terms	term	NOUN
flr-135	75	17	of	of	ADP
flr-135	75	18	accuracy	accuracy	NOUN
flr-135	75	19	(	(	PUNCT
flr-135	75	20	degree	degree	NOUN
flr-135	75	21	of	of	ADP
flr-135	75	22	similarity	similarity	NOUN
flr-135	75	23	between	between	ADP
flr-135	75	24	true	true	ADJ
flr-135	75	25	and	and	CCONJ
flr-135	75	26	estimated	estimated	ADJ
flr-135	75	27	variable	variable	ADJ
flr-135	75	28	ranks	rank	NOUN
flr-135	75	29	)	)	PUNCT
flr-135	75	30	and	and	CCONJ
flr-135	75	31	precision	precision	NOUN
flr-135	75	32	(	(	PUNCT
flr-135	75	33	degree	degree	NOUN
flr-135	75	34	of	of	ADP
flr-135	75	35	variation	variation	NOUN
flr-135	75	36	in	in	ADP
flr-135	75	37	accuracy	accuracy	NOUN
flr-135	75	38	)	)	PUNCT
flr-135	75	39	,	,	PUNCT
flr-135	75	40	when	when	SCONJ
flr-135	75	41	estimating	estimate	VERB
flr-135	75	42	the	the	DET
flr-135	75	43	true	true	ADJ
flr-135	75	44	importance	importance	NOUN
flr-135	75	45	of	of	ADP
flr-135	75	46	all	all	DET
flr-135	75	47	the	the	DET
flr-135	75	48	variables	variable	NOUN
flr-135	75	49	in	in	ADP
flr-135	75	50	the	the	DET
flr-135	75	51	ann	ann	PROPN
flr-135	75	52	.	.	PUNCT
flr-135	75	53	partial	partial	ADJ
flr-135	75	54	derivatives	derivative	NOUN
flr-135	75	55	,	,	PUNCT
flr-135	75	56	input	input	NOUN
flr-135	75	57	perturbation	perturbation	NOUN
flr-135	75	58	,	,	PUNCT
flr-135	75	59	sensitivity	sensitivity	NOUN
flr-135	75	60	analysis	analysis	NOUN
flr-135	75	61	and	and	CCONJ
flr-135	75	62	both	both	DET
flr-135	75	63	versions	version	NOUN
flr-135	75	64	of	of	ADP
flr-135	75	65	the	the	DET
flr-135	75	66	improved	improve	VERB
flr-135	75	67	stepwise	stepwise	NOUN
flr-135	75	68	selection	selection	NOUN
flr-135	75	69	methods	method	NOUN
flr-135	75	70	showed	show	VERB
flr-135	75	71	moderate	moderate	ADJ
flr-135	75	72	performance	performance	NOUN
flr-135	75	73	in	in	ADP
flr-135	75	74	the	the	DET
flr-135	75	75	simulations	simulation	NOUN
flr-135	75	76	.	.	PUNCT
flr-135	76	1	when	when	SCONJ
flr-135	76	2	estimating	estimate	VERB
flr-135	76	3	the	the	DET
flr-135	76	4	actual	actual	ADJ
flr-135	76	5	ranks	rank	NOUN
flr-135	76	6	,	,	PUNCT
flr-135	76	7	the	the	DET
flr-135	76	8	connection	connection	NOUN
flr-135	76	9	weights	weight	VERB
flr-135	76	10	approach	approach	NOUN
flr-135	76	11	once	once	ADV
flr-135	76	12	again	again	ADV
flr-135	76	13	was	be	AUX
flr-135	76	14	the	the	DET
flr-135	76	15	method	method	NOUN
flr-135	76	16	which	which	PRON
flr-135	76	17	exhibited	exhibit	VERB
flr-135	76	18	the	the	DET
flr-135	76	19	best	good	ADJ
flr-135	76	20	performance	performance	NOUN
flr-135	76	21	.	.	PUNCT
flr-135	77	1	in	in	ADP
flr-135	77	2	addition	addition	NOUN
flr-135	77	3	,	,	PUNCT
flr-135	77	4	olden	olden	ADJ
flr-135	77	5	and	and	CCONJ
flr-135	77	6	jackson	jackson	PROPN
flr-135	77	7	(	(	PUNCT
flr-135	77	8	2002	2002	NUM
flr-135	77	9	)	)	PUNCT
flr-135	77	10	reviewed	review	VERB
flr-135	77	11	a	a	DET
flr-135	77	12	randomisation	randomisation	NOUN
flr-135	77	13	approach	approach	NOUN
flr-135	77	14	to	to	AUX
flr-135	77	15	better	well	ADV
flr-135	77	16	evaluate	evaluate	VERB
flr-135	77	17	and	and	CCONJ
flr-135	77	18	understand	understand	VERB
flr-135	77	19	the	the	DET
flr-135	77	20	contribution	contribution	NOUN
flr-135	77	21	of	of	ADP
flr-135	77	22	predictors	predictor	NOUN
flr-135	77	23	in	in	ADP
flr-135	77	24	ann	ann	PROPN
flr-135	77	25	analysis	analysis	NOUN
flr-135	77	26	.	.	PUNCT
flr-135	78	1	they	they	PRON
flr-135	78	2	conclude	conclude	VERB
flr-135	78	3	by	by	ADP
flr-135	78	4	stating	state	VERB
flr-135	78	5	:	:	PUNCT
flr-135	78	6	“	"	PUNCT
flr-135	78	7	thus	thus	ADV
flr-135	78	8	,	,	PUNCT
flr-135	78	9	by	by	ADP
flr-135	78	10	coupling	couple	VERB
flr-135	78	11	this	this	DET
flr-135	78	12	new	new	ADJ
flr-135	78	13	explanatory	explanatory	ADJ
flr-135	78	14	power	power	NOUN
flr-135	78	15	of	of	ADP
flr-135	78	16	neural	neural	ADJ
flr-135	78	17	networks	network	NOUN
flr-135	78	18	with	with	ADP
flr-135	78	19	its	its	PRON
flr-135	78	20	strong	strong	ADJ
flr-135	78	21	predictive	predictive	ADJ
flr-135	78	22	abilities	ability	NOUN
flr-135	78	23	,	,	PUNCT
flr-135	78	24	anns	anns	NOUN
flr-135	78	25	promise	promise	NOUN
flr-135	78	26	to	to	PART
flr-135	78	27	be	be	AUX
flr-135	78	28	a	a	DET
flr-135	78	29	valuable	valuable	ADJ
flr-135	78	30	quantitative	quantitative	ADJ
flr-135	78	31	tool	tool	NOUN
flr-135	78	32	to	to	PART
flr-135	78	33	evaluate	evaluate	VERB
flr-135	78	34	,	,	PUNCT
flr-135	78	35	understand	understand	VERB
flr-135	78	36	,	,	PUNCT
flr-135	78	37	and	and	CCONJ
flr-135	78	38	predict	predict	VERB
flr-135	78	39	ecological	ecological	ADJ
flr-135	78	40	phenomena	phenomenon	NOUN
flr-135	78	41	”	"	PUNCT
flr-135	78	42	(	(	PUNCT
flr-135	78	43	olden	olden	PROPN
flr-135	78	44	&	&	CCONJ
flr-135	78	45	jackson	jackson	PROPN
flr-135	78	46	,	,	PUNCT
flr-135	78	47	2002	2002	NUM
flr-135	78	48	,	,	PUNCT
flr-135	78	49	p.	p.	NOUN
flr-135	78	50	135	135	NUM
flr-135	78	51	)	)	PUNCT
flr-135	78	52	.	.	PUNCT
flr-135	79	1	all	all	PRON
flr-135	79	2	of	of	ADP
flr-135	79	3	these	these	DET
flr-135	79	4	examples	example	NOUN
flr-135	79	5	demonstrate	demonstrate	VERB
flr-135	79	6	that	that	SCONJ
flr-135	79	7	using	use	VERB
flr-135	79	8	the	the	DET
flr-135	79	9	appropriate	appropriate	ADJ
flr-135	79	10	techniques	technique	NOUN
flr-135	79	11	,	,	PUNCT
flr-135	79	12	the	the	DET
flr-135	79	13	complexity	complexity	NOUN
flr-135	79	14	of	of	ADP
flr-135	79	15	an	an	DET
flr-135	79	16	ann	ann	PROPN
flr-135	79	17	does	do	AUX
flr-135	79	18	not	not	PART
flr-135	79	19	need	need	VERB
flr-135	79	20	to	to	PART
flr-135	79	21	translate	translate	VERB
flr-135	79	22	into	into	ADP
flr-135	79	23	“	"	PUNCT
flr-135	79	24	opacity	opacity	NOUN
flr-135	79	25	”	"	PUNCT
flr-135	79	26	,	,	PUNCT
flr-135	79	27	and	and	CCONJ
flr-135	79	28	researchers	researcher	NOUN
flr-135	79	29	are	be	AUX
flr-135	79	30	not	not	PART
flr-135	79	31	limited	limit	VERB
flr-135	79	32	in	in	ADP
flr-135	79	33	their	their	PRON
flr-135	79	34	ability	ability	NOUN
flr-135	79	35	to	to	PART
flr-135	79	36	gain	gain	VERB
flr-135	79	37	insight	insight	NOUN
flr-135	79	38	into	into	ADP
flr-135	79	39	the	the	DET
flr-135	79	40	explanatory	explanatory	ADJ
flr-135	79	41	factors	factor	NOUN
flr-135	79	42	of	of	ADP
flr-135	79	43	the	the	DET
flr-135	79	44	prediction	prediction	NOUN
flr-135	79	45	and	and	CCONJ
flr-135	79	46	classification	classification	NOUN
flr-135	79	47	processes	process	NOUN
flr-135	79	48	performed	perform	VERB
flr-135	79	49	efficiently	efficiently	ADV
flr-135	79	50	by	by	ADP
flr-135	79	51	anns	ann	NOUN
flr-135	79	52	.	.	PUNCT
flr-135	80	1	studies	study	NOUN
flr-135	80	2	such	such	ADJ
flr-135	80	3	as	as	ADP
flr-135	80	4	olden	olden	ADJ
flr-135	80	5	et	et	PROPN
flr-135	80	6	al	al	PROPN
flr-135	80	7	.	.	PROPN
flr-135	80	8	(	(	PUNCT
flr-135	80	9	2004	2004	NUM
flr-135	80	10	)	)	PUNCT
flr-135	80	11	,	,	PUNCT
flr-135	80	12	gevrey	gevrey	PROPN
flr-135	80	13	et	et	PROPN
flr-135	80	14	al	al	PROPN
flr-135	80	15	.	.	PROPN
flr-135	80	16	(	(	PUNCT
flr-135	80	17	2003	2003	NUM
flr-135	80	18	)	)	PUNCT
flr-135	80	19	,	,	PUNCT
flr-135	80	20	and	and	CCONJ
flr-135	80	21	lek	lek	PROPN
flr-135	80	22	,	,	PUNCT
flr-135	80	23	belaud	belaud	NOUN
flr-135	80	24	,	,	PUNCT
flr-135	80	25	baran	baran	NOUN
flr-135	80	26	,	,	PUNCT
flr-135	80	27	dimopoulos	dimopoulo	NOUN
flr-135	80	28	,	,	PUNCT
flr-135	80	29	and	and	CCONJ
flr-135	80	30	delacoste	delacoste	NOUN
flr-135	80	31	(	(	PUNCT
flr-135	80	32	1996	1996	NUM
flr-135	80	33	)	)	PUNCT
flr-135	80	34	,	,	PUNCT
flr-135	80	35	are	be	AUX
flr-135	80	36	but	but	CCONJ
flr-135	80	37	the	the	DET
flr-135	80	38	beginnings	beginning	NOUN
flr-135	80	39	of	of	ADP
flr-135	80	40	a	a	DET
flr-135	80	41	vast	vast	ADJ
flr-135	80	42	number	number	NOUN
flr-135	80	43	of	of	ADP
flr-135	80	44	applications	application	NOUN
flr-135	80	45	that	that	PRON
flr-135	80	46	have	have	AUX
flr-135	80	47	“	"	PUNCT
flr-135	80	48	opened	open	VERB
flr-135	80	49	the	the	DET
flr-135	80	50	box	box	NOUN
flr-135	80	51	”	"	PUNCT
flr-135	80	52	in	in	ADP
flr-135	80	53	ann	ann	PROPN
flr-135	80	54	analysis	analysis	NOUN
flr-135	80	55	.	.	PUNCT
flr-135	81	1	in	in	ADP
flr-135	81	2	addition	addition	NOUN
flr-135	81	3	,	,	PUNCT
flr-135	81	4	regularisation	regularisation	NOUN
flr-135	81	5	approaches	approach	NOUN
flr-135	81	6	have	have	AUX
flr-135	81	7	been	be	AUX
flr-135	81	8	used	use	VERB
flr-135	81	9	to	to	PART
flr-135	81	10	enhance	enhance	VERB
flr-135	81	11	the	the	DET
flr-135	81	12	interpretation	interpretation	NOUN
flr-135	81	13	of	of	ADP
flr-135	81	14	ann	ann	PROPN
flr-135	81	15	results	result	NOUN
flr-135	81	16	(	(	PUNCT
flr-135	81	17	intrator	intrator	NOUN
flr-135	81	18	&	&	CCONJ
flr-135	81	19	intrator	intrator	PROPN
flr-135	81	20	,	,	PUNCT
flr-135	81	21	2001	2001	NUM
flr-135	81	22	)	)	PUNCT
flr-135	81	23	,	,	PUNCT
flr-135	81	24	and	and	CCONJ
flr-135	81	25	the	the	DET
flr-135	81	26	estimation	estimation	NOUN
flr-135	81	27	of	of	ADP
flr-135	81	28	interaction	interaction	NOUN
flr-135	81	29	effects	effect	NOUN
flr-135	81	30	in	in	ADP
flr-135	81	31	anns	anns	NOUN
flr-135	81	32	was	be	AUX
flr-135	81	33	used	use	VERB
flr-135	81	34	and	and	CCONJ
flr-135	81	35	demonstrated	demonstrate	VERB
flr-135	81	36	by	by	ADP
flr-135	81	37	donaldson	donaldson	PROPN
flr-135	81	38	and	and	CCONJ
flr-135	81	39	kamstra	kamstra	PROPN
flr-135	81	40	(	(	PUNCT
flr-135	81	41	1999	1999	NUM
flr-135	81	42	)	)	PUNCT
flr-135	81	43	.	.	PUNCT
flr-135	82	1	therefore	therefore	ADV
flr-135	82	2	,	,	PUNCT
flr-135	82	3	contrary	contrary	ADV
flr-135	82	4	to	to	ADP
flr-135	82	5	what	what	PRON
flr-135	82	6	has	have	AUX
flr-135	82	7	been	be	AUX
flr-135	82	8	pointed	point	VERB
flr-135	82	9	out	out	ADP
flr-135	82	10	by	by	ADP
flr-135	82	11	edelsbrunner	edelsbrunner	NOUN
flr-135	82	12	and	and	CCONJ
flr-135	82	13	schneider	schneider	NOUN
flr-135	82	14	(	(	PUNCT
flr-135	82	15	2013	2013	NUM
flr-135	82	16	)	)	PUNCT
flr-135	82	17	and	and	CCONJ
flr-135	82	18	quoted	quote	VERB
flr-135	82	19	by	by	ADP
flr-135	82	20	golino	golino	NOUN
flr-135	82	21	and	and	CCONJ
flr-135	82	22	gomes	gome	NOUN
flr-135	82	23	(	(	PUNCT
flr-135	82	24	2014	2014	NUM
flr-135	82	25	)	)	PUNCT
flr-135	82	26	,	,	PUNCT
flr-135	82	27	the	the	DET
flr-135	82	28	ann	ann	PROPN
flr-135	82	29	approach	approach	NOUN
flr-135	82	30	offers	offer	VERB
flr-135	82	31	the	the	DET
flr-135	82	32	potential	potential	NOUN
flr-135	82	33	to	to	PART
flr-135	82	34	examine	examine	VERB
flr-135	82	35	the	the	DET
flr-135	82	36	complex	complex	ADJ
flr-135	82	37	relationships	relationship	NOUN
flr-135	82	38	amongst	amongst	ADP
flr-135	82	39	its	its	PRON
flr-135	82	40	components	component	NOUN
flr-135	82	41	.	.	PUNCT
flr-135	83	1	an	an	DET
flr-135	83	2	additional	additional	ADJ
flr-135	83	3	important	important	ADJ
flr-135	83	4	advantage	advantage	NOUN
flr-135	83	5	of	of	ADP
flr-135	83	6	ann	ann	PROPN
flr-135	83	7	analysis	analysis	NOUN
flr-135	83	8	refers	refer	VERB
flr-135	83	9	to	to	ADP
flr-135	83	10	the	the	DET
flr-135	83	11	need	need	NOUN
flr-135	83	12	to	to	PART
flr-135	83	13	capture	capture	VERB
flr-135	83	14	the	the	DET
flr-135	83	15	complexity	complexity	NOUN
flr-135	83	16	of	of	ADP
flr-135	83	17	the	the	DET
flr-135	83	18	interaction	interaction	NOUN
flr-135	83	19	of	of	ADP
flr-135	83	20	various	various	ADJ
flr-135	83	21	factors	factor	NOUN
flr-135	83	22	in	in	ADP
flr-135	83	23	the	the	DET
flr-135	83	24	understanding	understanding	NOUN
flr-135	83	25	of	of	ADP
flr-135	83	26	also	also	ADV
flr-135	83	27	complex	complex	ADJ
flr-135	83	28	phenomena	phenomenon	NOUN
flr-135	83	29	(	(	PUNCT
flr-135	83	30	agrawal	agrawal	PROPN
flr-135	83	31	,	,	PUNCT
flr-135	83	32	2001	2001	NUM
flr-135	83	33	)	)	PUNCT
flr-135	83	34	.	.	PUNCT
flr-135	84	1	it	it	PRON
flr-135	84	2	is	be	AUX
flr-135	84	3	difficult	difficult	ADJ
flr-135	84	4	to	to	PART
flr-135	84	5	find	find	VERB
flr-135	84	6	large	large	ADJ
flr-135	84	7	-	-	PUNCT
flr-135	84	8	n	n	NOUN
flr-135	84	9	studies	study	NOUN
flr-135	84	10	with	with	ADP
flr-135	84	11	a	a	DET
flr-135	84	12	large	large	ADJ
flr-135	84	13	set	set	NOUN
flr-135	84	14	of	of	ADP
flr-135	84	15	variables	variable	NOUN
flr-135	84	16	,	,	PUNCT
flr-135	84	17	particularly	particularly	ADV
flr-135	84	18	in	in	ADP
flr-135	84	19	the	the	DET
flr-135	84	20	social	social	ADJ
flr-135	84	21	and	and	CCONJ
flr-135	84	22	educational	educational	ADJ
flr-135	84	23	sciences	science	NOUN
flr-135	84	24	.	.	PUNCT
flr-135	85	1	so	so	ADV
flr-135	85	2	,	,	PUNCT
flr-135	85	3	most	most	ADJ
flr-135	85	4	studies	study	NOUN
flr-135	85	5	attempt	attempt	VERB
flr-135	85	6	to	to	PART
flr-135	85	7	develop	develop	VERB
flr-135	85	8	causal	causal	ADJ
flr-135	85	9	models	model	NOUN
flr-135	85	10	based	base	VERB
flr-135	85	11	on	on	ADP
flr-135	85	12	a	a	DET
flr-135	85	13	cascallar	cascallar	ADJ
flr-135	85	14	et	et	NOUN
flr-135	85	15	al	al	PROPN
flr-135	85	16	72	72	NUM
flr-135	86	1	|	|	CCONJ
flr-135	86	2	f	f	NOUN
flr-135	86	3	l	l	NOUN
flr-135	86	4	r	r	NOUN
flr-135	86	5	very	very	ADV
flr-135	86	6	limited	limited	ADJ
flr-135	86	7	set	set	NOUN
flr-135	86	8	of	of	ADP
flr-135	86	9	variables	variable	NOUN
flr-135	86	10	,	,	PUNCT
flr-135	86	11	without	without	ADP
flr-135	86	12	the	the	DET
flr-135	86	13	capacity	capacity	NOUN
flr-135	86	14	to	to	PART
flr-135	86	15	encompass	encompass	VERB
flr-135	86	16	a	a	DET
flr-135	86	17	large	large	ADJ
flr-135	86	18	number	number	NOUN
flr-135	86	19	of	of	ADP
flr-135	86	20	predictors	predictor	NOUN
flr-135	86	21	,	,	PUNCT
flr-135	86	22	and	and	CCONJ
flr-135	86	23	therefore	therefore	ADV
flr-135	86	24	not	not	PART
flr-135	86	25	providing	provide	VERB
flr-135	86	26	the	the	DET
flr-135	86	27	possibility	possibility	NOUN
flr-135	86	28	to	to	PART
flr-135	86	29	observe	observe	VERB
flr-135	86	30	their	their	PRON
flr-135	86	31	complex	complex	ADJ
flr-135	86	32	interactions	interaction	NOUN
flr-135	86	33	(	(	PUNCT
flr-135	86	34	boekaerts	boekaert	NOUN
flr-135	86	35	&	&	CCONJ
flr-135	86	36	cascallar	cascallar	ADJ
flr-135	86	37	,	,	PUNCT
flr-135	86	38	2006	2006	NUM
flr-135	86	39	;	;	PUNCT
flr-135	86	40	cascallar	cascallar	PROPN
flr-135	86	41	et	et	PROPN
flr-135	86	42	al	al	PROPN
flr-135	86	43	.	.	PROPN
flr-135	86	44	,	,	PUNCT
flr-135	86	45	2006	2006	NUM
flr-135	86	46	)	)	PUNCT
flr-135	86	47	.	.	PUNCT
flr-135	87	1	a	a	DET
flr-135	87	2	resulting	result	VERB
flr-135	87	3	problem	problem	NOUN
flr-135	87	4	is	be	AUX
flr-135	87	5	that	that	SCONJ
flr-135	87	6	meta	meta	ADJ
flr-135	87	7	-	-	PUNCT
flr-135	87	8	analyses	analysis	NOUN
flr-135	87	9	trying	try	VERB
flr-135	87	10	to	to	PART
flr-135	87	11	find	find	VERB
flr-135	87	12	general	general	ADJ
flr-135	87	13	statistical	statistical	ADJ
flr-135	87	14	correlations	correlation	NOUN
flr-135	87	15	face	face	VERB
flr-135	87	16	very	very	ADV
flr-135	87	17	serious	serious	ADJ
flr-135	87	18	problems	problem	NOUN
flr-135	87	19	as	as	SCONJ
flr-135	87	20	interactions	interaction	NOUN
flr-135	87	21	between	between	ADP
flr-135	87	22	the	the	DET
flr-135	87	23	factors	factor	NOUN
flr-135	87	24	analysed	analyse	VERB
flr-135	87	25	are	be	AUX
flr-135	87	26	not	not	PART
flr-135	87	27	known	know	VERB
flr-135	87	28	,	,	PUNCT
flr-135	87	29	which	which	PRON
flr-135	87	30	in	in	ADP
flr-135	87	31	turn	turn	NOUN
flr-135	87	32	leads	lead	VERB
flr-135	87	33	to	to	ADP
flr-135	87	34	wrong	wrong	ADJ
flr-135	87	35	estimations	estimation	NOUN
flr-135	87	36	of	of	ADP
flr-135	87	37	relevance	relevance	NOUN
flr-135	87	38	.	.	PUNCT
flr-135	88	1	related	relate	VERB
flr-135	88	2	to	to	ADP
flr-135	88	3	this	this	DET
flr-135	88	4	problem	problem	NOUN
flr-135	88	5	is	be	AUX
flr-135	88	6	the	the	DET
flr-135	88	7	fact	fact	NOUN
flr-135	88	8	that	that	SCONJ
flr-135	88	9	in	in	ADP
flr-135	88	10	all	all	DET
flr-135	88	11	studies	study	NOUN
flr-135	88	12	that	that	PRON
flr-135	88	13	knowingly	knowingly	ADV
flr-135	88	14	or	or	CCONJ
flr-135	88	15	unknowingly	unknowingly	ADV
flr-135	88	16	exclude	exclude	VERB
flr-135	88	17	a	a	DET
flr-135	88	18	relevant	relevant	ADJ
flr-135	88	19	factor	factor	NOUN
flr-135	88	20	,	,	PUNCT
flr-135	88	21	the	the	DET
flr-135	88	22	importance	importance	NOUN
flr-135	88	23	of	of	ADP
flr-135	88	24	all	all	DET
flr-135	88	25	other	other	ADJ
flr-135	88	26	variables	variable	NOUN
flr-135	88	27	shifts	shift	NOUN
flr-135	88	28	dramatically	dramatically	ADV
flr-135	88	29	.	.	PUNCT
flr-135	89	1	this	this	DET
flr-135	89	2	effect	effect	NOUN
flr-135	89	3	has	have	AUX
flr-135	89	4	been	be	AUX
flr-135	89	5	noted	note	VERB
flr-135	89	6	in	in	ADP
flr-135	89	7	very	very	ADV
flr-135	89	8	diverse	diverse	ADJ
flr-135	89	9	fields	field	NOUN
flr-135	89	10	ranging	range	VERB
flr-135	89	11	from	from	ADP
flr-135	89	12	natural	natural	ADJ
flr-135	89	13	resource	resource	NOUN
flr-135	89	14	estimation	estimation	NOUN
flr-135	89	15	to	to	ADP
flr-135	89	16	self	self	NOUN
flr-135	89	17	-	-	PUNCT
flr-135	89	18	regulated	regulate	VERB
flr-135	89	19	learning	learning	NOUN
flr-135	89	20	(	(	PUNCT
flr-135	89	21	agrawal	agrawal	PROPN
flr-135	89	22	&	&	CCONJ
flr-135	89	23	chhatre	chhatre	PROPN
flr-135	89	24	,	,	PUNCT
flr-135	89	25	2006	2006	NUM
flr-135	89	26	;	;	PUNCT
flr-135	89	27	boekaerts	boekaert	NOUN
flr-135	89	28	&	&	CCONJ
flr-135	89	29	cascallar	cascallar	ADJ
flr-135	89	30	,	,	PUNCT
flr-135	89	31	2006	2006	NUM
flr-135	89	32	)	)	PUNCT
flr-135	89	33	.	.	PUNCT
flr-135	90	1	studies	study	NOUN
flr-135	90	2	which	which	PRON
flr-135	90	3	only	only	ADV
flr-135	90	4	take	take	VERB
flr-135	90	5	into	into	ADP
flr-135	90	6	account	account	NOUN
flr-135	90	7	a	a	DET
flr-135	90	8	few	few	ADJ
flr-135	90	9	variables	variable	NOUN
flr-135	90	10	,	,	PUNCT
flr-135	90	11	in	in	ADP
flr-135	90	12	rather	rather	ADV
flr-135	90	13	simple	simple	ADJ
flr-135	90	14	designs	design	NOUN
flr-135	90	15	,	,	PUNCT
flr-135	90	16	and	and	CCONJ
flr-135	90	17	do	do	AUX
flr-135	90	18	not	not	PART
flr-135	90	19	consider	consider	VERB
flr-135	90	20	very	very	ADV
flr-135	90	21	important	important	ADJ
flr-135	90	22	but	but	CCONJ
flr-135	90	23	complex	complex	ADJ
flr-135	90	24	interactions	interaction	NOUN
flr-135	90	25	with	with	ADP
flr-135	90	26	a	a	DET
flr-135	90	27	larger	large	ADJ
flr-135	90	28	number	number	NOUN
flr-135	90	29	of	of	ADP
flr-135	90	30	participating	participate	VERB
flr-135	90	31	factors	factor	NOUN
flr-135	90	32	can	can	AUX
flr-135	90	33	and	and	CCONJ
flr-135	90	34	do	do	AUX
flr-135	90	35	often	often	ADV
flr-135	90	36	show	show	VERB
flr-135	90	37	contradictory	contradictory	ADJ
flr-135	90	38	results	result	NOUN
flr-135	90	39	.	.	PUNCT
flr-135	91	1	this	this	PRON
flr-135	91	2	should	should	AUX
flr-135	91	3	not	not	PART
flr-135	91	4	be	be	AUX
flr-135	91	5	considered	consider	VERB
flr-135	91	6	a	a	DET
flr-135	91	7	trivial	trivial	ADJ
flr-135	91	8	problem	problem	NOUN
flr-135	91	9	for	for	ADP
flr-135	91	10	the	the	DET
flr-135	91	11	conceptualisation	conceptualisation	NOUN
flr-135	91	12	of	of	ADP
flr-135	91	13	various	various	ADJ
flr-135	91	14	effects	effect	NOUN
flr-135	91	15	and	and	CCONJ
flr-135	91	16	phenomena	phenomenon	NOUN
flr-135	91	17	in	in	ADP
flr-135	91	18	every	every	DET
flr-135	91	19	scientific	scientific	ADJ
flr-135	91	20	field	field	NOUN
flr-135	91	21	(	(	PUNCT
flr-135	91	22	boekaerts	boekaert	NOUN
flr-135	91	23	&	&	CCONJ
flr-135	91	24	cascallar	cascallar	ADJ
flr-135	91	25	,	,	PUNCT
flr-135	91	26	2006	2006	NUM
flr-135	91	27	)	)	PUNCT
flr-135	91	28	.	.	PUNCT
flr-135	92	1	frey	frey	PROPN
flr-135	92	2	and	and	CCONJ
flr-135	92	3	rusch	rusch	PROPN
flr-135	92	4	(	(	PUNCT
flr-135	92	5	2013	2013	NUM
flr-135	92	6	)	)	PUNCT
flr-135	92	7	present	present	VERB
flr-135	92	8	an	an	DET
flr-135	92	9	interesting	interesting	ADJ
flr-135	92	10	study	study	NOUN
flr-135	92	11	in	in	ADP
flr-135	92	12	the	the	DET
flr-135	92	13	area	area	NOUN
flr-135	92	14	of	of	ADP
flr-135	92	15	social	social	ADJ
flr-135	92	16	-	-	PUNCT
flr-135	92	17	ecological	ecological	ADJ
flr-135	92	18	systems	system	NOUN
flr-135	92	19	which	which	PRON
flr-135	92	20	uses	use	VERB
flr-135	92	21	anns	anns	NOUN
flr-135	92	22	with	with	ADP
flr-135	92	23	an	an	DET
flr-135	92	24	analytic	analytic	ADJ
flr-135	92	25	approach	approach	NOUN
flr-135	92	26	that	that	PRON
flr-135	92	27	produces	produce	VERB
flr-135	92	28	an	an	DET
flr-135	92	29	open	open	ADJ
flr-135	92	30	architecture	architecture	NOUN
flr-135	92	31	in	in	ADP
flr-135	92	32	which	which	PRON
flr-135	92	33	it	it	PRON
flr-135	92	34	is	be	AUX
flr-135	92	35	possible	possible	ADJ
flr-135	92	36	to	to	PART
flr-135	92	37	establish	establish	VERB
flr-135	92	38	the	the	DET
flr-135	92	39	input	input	NOUN
flr-135	92	40	-	-	PUNCT
flr-135	92	41	output	output	NOUN
flr-135	92	42	relationships	relationship	NOUN
flr-135	92	43	which	which	PRON
flr-135	92	44	edelsbrunner	edelsbrunner	NOUN
flr-135	92	45	and	and	CCONJ
flr-135	92	46	schneider	schneider	NOUN
flr-135	92	47	(	(	PUNCT
flr-135	92	48	2013	2013	NUM
flr-135	92	49	)	)	PUNCT
flr-135	92	50	seem	seem	VERB
flr-135	92	51	to	to	PART
flr-135	92	52	perceive	perceive	VERB
flr-135	92	53	are	be	AUX
flr-135	92	54	unachievable	unachievable	ADJ
flr-135	92	55	for	for	ADP
flr-135	92	56	anns	ann	NOUN
flr-135	92	57	.	.	PUNCT
flr-135	93	1	these	these	DET
flr-135	93	2	analyses	analysis	NOUN
flr-135	93	3	suggested	suggest	VERB
flr-135	93	4	by	by	ADP
flr-135	93	5	various	various	ADJ
flr-135	93	6	authors	author	NOUN
flr-135	93	7	(	(	PUNCT
flr-135	93	8	thrush	thrush	NOUN
flr-135	93	9	,	,	PUNCT
flr-135	93	10	coco	coco	PROPN
flr-135	93	11	&	&	CCONJ
flr-135	93	12	hewitt	hewitt	PROPN
flr-135	93	13	,	,	PUNCT
flr-135	93	14	2008	2008	NUM
flr-135	93	15	;	;	PUNCT
flr-135	93	16	yeh	yeh	PROPN
flr-135	93	17	&	&	CCONJ
flr-135	93	18	cheng	cheng	PROPN
flr-135	93	19	2010	2010	NUM
flr-135	93	20	)	)	PUNCT
flr-135	93	21	make	make	VERB
flr-135	93	22	the	the	DET
flr-135	93	23	relationships	relationship	NOUN
flr-135	93	24	among	among	ADP
flr-135	93	25	the	the	DET
flr-135	93	26	various	various	ADJ
flr-135	93	27	input	input	NOUN
flr-135	93	28	-	-	PUNCT
flr-135	93	29	output	output	NOUN
flr-135	93	30	variables	variable	NOUN
flr-135	93	31	explicit	explicit	ADJ
flr-135	93	32	.	.	PUNCT
flr-135	94	1	the	the	DET
flr-135	94	2	second	second	ADJ
flr-135	94	3	main	main	ADJ
flr-135	94	4	argument	argument	NOUN
flr-135	94	5	regarding	regard	VERB
flr-135	94	6	problems	problem	NOUN
flr-135	94	7	associated	associate	VERB
flr-135	94	8	with	with	ADP
flr-135	94	9	the	the	DET
flr-135	94	10	ann	ann	PROPN
flr-135	94	11	methodology	methodology	NOUN
flr-135	94	12	,	,	PUNCT
flr-135	94	13	as	as	SCONJ
flr-135	94	14	claimed	claim	VERB
flr-135	94	15	by	by	ADP
flr-135	94	16	edelsbrunner	edelsbrunner	NOUN
flr-135	94	17	and	and	CCONJ
flr-135	94	18	schneider	schneider	NOUN
flr-135	94	19	(	(	PUNCT
flr-135	94	20	2013	2013	NUM
flr-135	94	21	)	)	PUNCT
flr-135	94	22	,	,	PUNCT
flr-135	94	23	has	have	VERB
flr-135	94	24	to	to	PART
flr-135	94	25	do	do	VERB
flr-135	94	26	with	with	ADP
flr-135	94	27	the	the	DET
flr-135	94	28	lack	lack	NOUN
flr-135	94	29	of	of	ADP
flr-135	94	30	some	some	DET
flr-135	94	31	statistical	statistical	ADJ
flr-135	94	32	parameters	parameter	NOUN
flr-135	94	33	in	in	ADP
flr-135	94	34	anns	ann	NOUN
flr-135	94	35	.	.	PUNCT
flr-135	95	1	this	this	PRON
flr-135	95	2	ignores	ignore	VERB
flr-135	95	3	the	the	DET
flr-135	95	4	evidence	evidence	NOUN
flr-135	95	5	that	that	SCONJ
flr-135	95	6	there	there	PRON
flr-135	95	7	has	have	AUX
flr-135	95	8	also	also	ADV
flr-135	95	9	been	be	AUX
flr-135	95	10	an	an	DET
flr-135	95	11	abundance	abundance	NOUN
flr-135	95	12	of	of	ADP
flr-135	95	13	research	research	NOUN
flr-135	95	14	to	to	PART
flr-135	95	15	provide	provide	VERB
flr-135	95	16	the	the	DET
flr-135	95	17	ann	ann	PROPN
flr-135	95	18	model	model	NOUN
flr-135	95	19	with	with	ADP
flr-135	95	20	equivalent	equivalent	ADJ
flr-135	95	21	information	information	NOUN
flr-135	95	22	.	.	PUNCT
flr-135	96	1	there	there	PRON
flr-135	96	2	have	have	AUX
flr-135	96	3	been	be	AUX
flr-135	96	4	increasing	increase	VERB
flr-135	96	5	efforts	effort	NOUN
flr-135	96	6	for	for	ADP
flr-135	96	7	some	some	DET
flr-135	96	8	time	time	NOUN
flr-135	96	9	,	,	PUNCT
flr-135	96	10	to	to	PART
flr-135	96	11	embed	embed	VERB
flr-135	96	12	anns	ann	NOUN
flr-135	96	13	in	in	ADP
flr-135	96	14	general	general	ADJ
flr-135	96	15	statistical	statistical	ADJ
flr-135	96	16	frameworks	framework	NOUN
flr-135	96	17	(	(	PUNCT
flr-135	96	18	cheng	cheng	PROPN
flr-135	96	19	&	&	CCONJ
flr-135	96	20	titterington	titterington	PROPN
flr-135	96	21	,	,	PUNCT
flr-135	96	22	1994	1994	NUM
flr-135	96	23	)	)	PUNCT
flr-135	96	24	,	,	PUNCT
flr-135	96	25	with	with	ADP
flr-135	96	26	bridle	bridle	NOUN
flr-135	96	27	(	(	PUNCT
flr-135	96	28	1992	1992	NUM
flr-135	96	29	)	)	PUNCT
flr-135	96	30	comparing	compare	VERB
flr-135	96	31	and	and	CCONJ
flr-135	96	32	blending	blend	VERB
flr-135	96	33	anns	ann	NOUN
flr-135	96	34	with	with	ADP
flr-135	96	35	markov	markov	NOUN
flr-135	96	36	-	-	PUNCT
flr-135	96	37	chain	chain	NOUN
flr-135	96	38	models	model	NOUN
flr-135	96	39	,	,	PUNCT
flr-135	96	40	and	and	CCONJ
flr-135	96	41	applying	apply	VERB
flr-135	96	42	bayesian	bayesian	NOUN
flr-135	96	43	approaches	approach	NOUN
flr-135	96	44	and	and	CCONJ
flr-135	96	45	methods	method	NOUN
flr-135	96	46	in	in	ADP
flr-135	96	47	the	the	DET
flr-135	96	48	modelling	modelling	NOUN
flr-135	96	49	of	of	ADP
flr-135	96	50	neural	neural	ADJ
flr-135	96	51	networks	network	NOUN
flr-135	96	52	(	(	PUNCT
flr-135	96	53	mackay	mackay	PROPN
flr-135	96	54	,	,	PUNCT
flr-135	96	55	1992	1992	NUM
flr-135	96	56	)	)	PUNCT
flr-135	96	57	.	.	PUNCT
flr-135	97	1	more	more	ADV
flr-135	97	2	recently	recently	ADV
flr-135	97	3	,	,	PUNCT
flr-135	97	4	he	he	PRON
flr-135	97	5	and	and	CCONJ
flr-135	97	6	li	li	PROPN
flr-135	97	7	(	(	PUNCT
flr-135	97	8	2011	2011	NUM
flr-135	97	9	)	)	PUNCT
flr-135	97	10	provide	provide	VERB
flr-135	97	11	an	an	DET
flr-135	97	12	interesting	interesting	ADJ
flr-135	97	13	example	example	NOUN
flr-135	97	14	of	of	ADP
flr-135	97	15	such	such	ADJ
flr-135	97	16	work	work	NOUN
flr-135	97	17	.	.	PUNCT
flr-135	98	1	they	they	PRON
flr-135	98	2	used	use	VERB
flr-135	98	3	the	the	DET
flr-135	98	4	standard	standard	ADJ
flr-135	98	5	backpropagation	backpropagation	NOUN
flr-135	98	6	algorithm	algorithm	NOUN
flr-135	98	7	derived	derive	VERB
flr-135	98	8	in	in	ADP
flr-135	98	9	vector	vector	NOUN
flr-135	98	10	form	form	NOUN
flr-135	98	11	,	,	PUNCT
flr-135	98	12	and	and	CCONJ
flr-135	98	13	they	they	PRON
flr-135	98	14	were	be	AUX
flr-135	98	15	successful	successful	ADJ
flr-135	98	16	in	in	ADP
flr-135	98	17	determining	determine	VERB
flr-135	98	18	the	the	DET
flr-135	98	19	confidence	confidence	NOUN
flr-135	98	20	interval	interval	NOUN
flr-135	98	21	and	and	CCONJ
flr-135	98	22	prediction	prediction	NOUN
flr-135	98	23	intervals	interval	NOUN
flr-135	98	24	for	for	ADP
flr-135	98	25	the	the	DET
flr-135	98	26	ann	ann	PROPN
flr-135	98	27	,	,	PUNCT
flr-135	98	28	while	while	SCONJ
flr-135	98	29	also	also	ADV
flr-135	98	30	exploring	explore	VERB
flr-135	98	31	which	which	DET
flr-135	98	32	neural	neural	ADJ
flr-135	98	33	network	network	NOUN
flr-135	98	34	structural	structural	ADJ
flr-135	98	35	characteristics	characteristic	NOUN
flr-135	98	36	had	have	VERB
flr-135	98	37	more	more	ADJ
flr-135	98	38	of	of	ADP
flr-135	98	39	an	an	DET
flr-135	98	40	impact	impact	NOUN
flr-135	98	41	on	on	ADP
flr-135	98	42	such	such	ADJ
flr-135	98	43	parameters	parameter	NOUN
flr-135	98	44	.	.	PUNCT
flr-135	99	1	in	in	ADP
flr-135	99	2	particular	particular	ADJ
flr-135	99	3	,	,	PUNCT
flr-135	99	4	when	when	SCONJ
flr-135	99	5	the	the	DET
flr-135	99	6	levenberg	levenberg	PROPN
flr-135	99	7	-	-	PUNCT
flr-135	99	8	marquardt	marquardt	PROPN
flr-135	99	9	backpropagation	backpropagation	NOUN
flr-135	99	10	algorithm	algorithm	NOUN
flr-135	99	11	is	be	AUX
flr-135	99	12	used	use	VERB
flr-135	99	13	to	to	PART
flr-135	99	14	train	train	VERB
flr-135	99	15	a	a	DET
flr-135	99	16	neural	neural	ADJ
flr-135	99	17	network	network	NOUN
flr-135	99	18	,	,	PUNCT
flr-135	99	19	since	since	SCONJ
flr-135	99	20	the	the	DET
flr-135	99	21	jacobian	jacobian	ADJ
flr-135	99	22	matrix	matrix	NOUN
flr-135	99	23	has	have	AUX
flr-135	99	24	been	be	AUX
flr-135	99	25	calculated	calculate	VERB
flr-135	99	26	to	to	PART
flr-135	99	27	update	update	VERB
flr-135	99	28	the	the	DET
flr-135	99	29	weights	weight	NOUN
flr-135	99	30	and	and	CCONJ
flr-135	99	31	biases	bias	NOUN
flr-135	99	32	of	of	ADP
flr-135	99	33	the	the	DET
flr-135	99	34	neural	neural	ADJ
flr-135	99	35	network	network	NOUN
flr-135	99	36	,	,	PUNCT
flr-135	99	37	the	the	DET
flr-135	99	38	confidence	confidence	NOUN
flr-135	99	39	interval	interval	NOUN
flr-135	99	40	with	with	ADP
flr-135	99	41	the	the	DET
flr-135	99	42	corresponding	correspond	VERB
flr-135	99	43	confidence	confidence	NOUN
flr-135	99	44	level	level	NOUN
flr-135	99	45	can	can	AUX
flr-135	99	46	be	be	AUX
flr-135	99	47	computed	compute	VERB
flr-135	99	48	to	to	PART
flr-135	99	49	evaluate	evaluate	VERB
flr-135	99	50	the	the	DET
flr-135	99	51	predictive	predictive	ADJ
flr-135	99	52	capability	capability	NOUN
flr-135	99	53	of	of	ADP
flr-135	99	54	the	the	DET
flr-135	99	55	ann	ann	PROPN
flr-135	99	56	.	.	PUNCT
flr-135	100	1	in	in	ADP
flr-135	100	2	addition	addition	NOUN
flr-135	100	3	,	,	PUNCT
flr-135	100	4	on	on	ADP
flr-135	100	5	similar	similar	ADJ
flr-135	100	6	topics	topic	NOUN
flr-135	100	7	,	,	PUNCT
flr-135	100	8	zapranis	zaprani	NOUN
flr-135	100	9	and	and	CCONJ
flr-135	100	10	livanis	livanis	PROPN
flr-135	100	11	(	(	PUNCT
flr-135	100	12	2005	2005	NUM
flr-135	100	13	)	)	PUNCT
flr-135	100	14	state	state	NOUN
flr-135	100	15	that	that	PRON
flr-135	100	16	given	give	VERB
flr-135	100	17	that	that	DET
flr-135	100	18	anns	anns	NOUN
flr-135	100	19	are	be	AUX
flr-135	100	20	a	a	DET
flr-135	100	21	good	good	ADJ
flr-135	100	22	example	example	NOUN
flr-135	100	23	of	of	ADP
flr-135	100	24	consistent	consistent	ADJ
flr-135	100	25	non	non	ADJ
flr-135	100	26	-	-	ADJ
flr-135	100	27	parametric	parametric	ADJ
flr-135	100	28	estimators	estimator	NOUN
flr-135	100	29	with	with	ADP
flr-135	100	30	powerful	powerful	ADJ
flr-135	100	31	universal	universal	ADJ
flr-135	100	32	approximation	approximation	NOUN
flr-135	100	33	properties	property	NOUN
flr-135	100	34	,	,	PUNCT
flr-135	100	35	they	they	PRON
flr-135	100	36	require	require	VERB
flr-135	100	37	that	that	SCONJ
flr-135	100	38	the	the	DET
flr-135	100	39	development	development	NOUN
flr-135	100	40	and	and	CCONJ
flr-135	100	41	implementation	implementation	NOUN
flr-135	100	42	of	of	ADP
flr-135	100	43	neural	neural	ADJ
flr-135	100	44	network	network	NOUN
flr-135	100	45	applications	application	NOUN
flr-135	100	46	has	have	VERB
flr-135	100	47	to	to	PART
flr-135	100	48	be	be	AUX
flr-135	100	49	based	base	VERB
flr-135	100	50	on	on	ADP
flr-135	100	51	established	establish	VERB
flr-135	100	52	procedures	procedure	NOUN
flr-135	100	53	for	for	ADP
flr-135	100	54	estimating	estimate	VERB
flr-135	100	55	confidence	confidence	NOUN
flr-135	100	56	and	and	CCONJ
flr-135	100	57	especially	especially	ADV
flr-135	100	58	prediction	prediction	NOUN
flr-135	100	59	intervals	interval	NOUN
flr-135	100	60	.	.	PUNCT
flr-135	101	1	they	they	PRON
flr-135	101	2	go	go	VERB
flr-135	101	3	on	on	ADP
flr-135	101	4	to	to	PART
flr-135	101	5	review	review	VERB
flr-135	101	6	the	the	DET
flr-135	101	7	main	main	ADJ
flr-135	101	8	state	state	NOUN
flr-135	101	9	-	-	PUNCT
flr-135	101	10	of	of	ADP
flr-135	101	11	-	-	PUNCT
flr-135	101	12	the	the	DET
flr-135	101	13	-	-	PUNCT
flr-135	101	14	art	art	NOUN
flr-135	101	15	approaches	approach	NOUN
flr-135	101	16	for	for	ADP
flr-135	101	17	the	the	DET
flr-135	101	18	construction	construction	NOUN
flr-135	101	19	of	of	ADP
flr-135	101	20	confidence	confidence	NOUN
flr-135	101	21	and	and	CCONJ
flr-135	101	22	prediction	prediction	NOUN
flr-135	101	23	intervals	interval	NOUN
flr-135	101	24	,	,	PUNCT
flr-135	101	25	and	and	CCONJ
flr-135	101	26	evaluate	evaluate	VERB
flr-135	101	27	their	their	PRON
flr-135	101	28	strengths	strength	NOUN
flr-135	101	29	and	and	CCONJ
flr-135	101	30	weaknesses	weakness	NOUN
flr-135	101	31	.	.	PUNCT
flr-135	102	1	after	after	ADP
flr-135	102	2	comparing	compare	VERB
flr-135	102	3	them	they	PRON
flr-135	102	4	in	in	ADP
flr-135	102	5	a	a	DET
flr-135	102	6	controlled	control	VERB
flr-135	102	7	simulation	simulation	NOUN
flr-135	102	8	,	,	PUNCT
flr-135	102	9	the	the	DET
flr-135	102	10	authors	author	NOUN
flr-135	102	11	suggest	suggest	VERB
flr-135	102	12	that	that	SCONJ
flr-135	102	13	a	a	DET
flr-135	102	14	combination	combination	NOUN
flr-135	102	15	of	of	ADP
flr-135	102	16	bootstrap	bootstrap	NOUN
flr-135	102	17	and	and	CCONJ
flr-135	102	18	maximum	maximum	ADJ
flr-135	102	19	likelihood	likelihood	NOUN
flr-135	102	20	approaches	approach	NOUN
flr-135	102	21	are	be	AUX
flr-135	102	22	superior	superior	ADJ
flr-135	102	23	to	to	ADP
flr-135	102	24	analytic	analytic	ADJ
flr-135	102	25	approaches	approach	NOUN
flr-135	102	26	when	when	SCONJ
flr-135	102	27	constructing	construct	VERB
flr-135	102	28	the	the	DET
flr-135	102	29	prediction	prediction	NOUN
flr-135	102	30	intervals	interval	NOUN
flr-135	102	31	(	(	PUNCT
flr-135	102	32	zapranis	zapranis	PROPN
flr-135	102	33	&	&	CCONJ
flr-135	102	34	livanis	livanis	PROPN
flr-135	102	35	,	,	PUNCT
flr-135	102	36	2005	2005	NUM
flr-135	102	37	)	)	PUNCT
flr-135	102	38	.	.	PUNCT
flr-135	103	1	on	on	ADP
flr-135	103	2	the	the	DET
flr-135	103	3	other	other	ADJ
flr-135	103	4	hand	hand	NOUN
flr-135	103	5	,	,	PUNCT
flr-135	103	6	other	other	ADJ
flr-135	103	7	authors	author	NOUN
flr-135	103	8	propose	propose	VERB
flr-135	103	9	the	the	DET
flr-135	103	10	construction	construction	NOUN
flr-135	103	11	of	of	ADP
flr-135	103	12	confidence	confidence	NOUN
flr-135	103	13	intervals	interval	NOUN
flr-135	103	14	for	for	ADP
flr-135	103	15	neural	neural	ADJ
flr-135	103	16	networks	network	NOUN
flr-135	103	17	based	base	VERB
flr-135	103	18	on	on	ADP
flr-135	103	19	least	least	ADJ
flr-135	103	20	squares	square	NOUN
flr-135	103	21	cascallar	cascallar	ADJ
flr-135	103	22	et	et	PROPN
flr-135	103	23	al	al	PROPN
flr-135	103	24	73	73	NUM
flr-135	104	1	|	|	ADV
flr-135	104	2	f	f	NOUN
flr-135	104	3	l	l	NOUN
flr-135	104	4	r	r	NOUN
flr-135	104	5	estimations	estimation	NOUN
flr-135	104	6	and	and	CCONJ
flr-135	104	7	using	use	VERB
flr-135	104	8	the	the	DET
flr-135	104	9	linear	linear	PROPN
flr-135	104	10	taylor	taylor	PROPN
flr-135	104	11	expansion	expansion	NOUN
flr-135	104	12	of	of	ADP
flr-135	104	13	the	the	DET
flr-135	104	14	nonlinear	nonlinear	ADJ
flr-135	104	15	model	model	NOUN
flr-135	104	16	output	output	NOUN
flr-135	104	17	,	,	PUNCT
flr-135	104	18	which	which	PRON
flr-135	104	19	also	also	ADV
flr-135	104	20	detects	detect	VERB
flr-135	104	21	ill	ill	ADJ
flr-135	104	22	-	-	PUNCT
flr-135	104	23	conditioning	conditioning	NOUN
flr-135	104	24	of	of	ADP
flr-135	104	25	ann	ann	PROPN
flr-135	104	26	candidates	candidate	NOUN
flr-135	104	27	and	and	CCONJ
flr-135	104	28	can	can	AUX
flr-135	104	29	estimate	estimate	VERB
flr-135	104	30	their	their	PRON
flr-135	104	31	performance	performance	NOUN
flr-135	104	32	(	(	PUNCT
flr-135	104	33	rivals	rival	NOUN
flr-135	104	34	and	and	CCONJ
flr-135	104	35	personnaz	personnaz	NOUN
flr-135	104	36	,	,	PUNCT
flr-135	104	37	2000	2000	NUM
flr-135	104	38	)	)	PUNCT
flr-135	104	39	.	.	PUNCT
flr-135	105	1	in	in	ADP
flr-135	105	2	terms	term	NOUN
flr-135	105	3	of	of	ADP
flr-135	105	4	the	the	DET
flr-135	105	5	comparison	comparison	NOUN
flr-135	105	6	between	between	ADP
flr-135	105	7	anns	anns	NOUN
flr-135	105	8	and	and	CCONJ
flr-135	105	9	logistic	logistic	ADJ
flr-135	105	10	regression	regression	NOUN
flr-135	105	11	,	,	PUNCT
flr-135	105	12	in	in	ADP
flr-135	105	13	neural	neural	ADJ
flr-135	105	14	network	network	NOUN
flr-135	105	15	analysis	analysis	NOUN
flr-135	105	16	the	the	DET
flr-135	105	17	purpose	purpose	NOUN
flr-135	105	18	of	of	ADP
flr-135	105	19	the	the	DET
flr-135	105	20	hidden	hide	VERB
flr-135	105	21	layer	layer	NOUN
flr-135	105	22	is	be	AUX
flr-135	105	23	to	to	PART
flr-135	105	24	map	map	VERB
flr-135	105	25	a	a	DET
flr-135	105	26	set	set	NOUN
flr-135	105	27	of	of	ADP
flr-135	105	28	patterns	pattern	NOUN
flr-135	105	29	,	,	PUNCT
flr-135	105	30	which	which	PRON
flr-135	105	31	are	be	AUX
flr-135	105	32	linearly	linearly	ADV
flr-135	105	33	non	non	ADJ
flr-135	105	34	-	-	ADJ
flr-135	105	35	separable	separable	ADJ
flr-135	105	36	in	in	ADP
flr-135	105	37	the	the	DET
flr-135	105	38	input	input	NOUN
flr-135	105	39	space	space	NOUN
flr-135	105	40	,	,	PUNCT
flr-135	105	41	into	into	ADP
flr-135	105	42	the	the	DET
flr-135	105	43	so	so	ADV
flr-135	105	44	-	-	PUNCT
flr-135	105	45	called	call	VERB
flr-135	105	46	image	image	NOUN
flr-135	105	47	-	-	PUNCT
flr-135	105	48	space	space	NOUN
flr-135	105	49	in	in	ADP
flr-135	105	50	the	the	DET
flr-135	105	51	hidden	hide	VERB
flr-135	105	52	layer	layer	NOUN
flr-135	105	53	,	,	PUNCT
flr-135	105	54	where	where	SCONJ
flr-135	105	55	these	these	DET
flr-135	105	56	patterns	pattern	NOUN
flr-135	105	57	may	may	AUX
flr-135	105	58	become	become	VERB
flr-135	105	59	linearly	linearly	ADV
flr-135	105	60	separable	separable	ADJ
flr-135	105	61	.	.	PUNCT
flr-135	106	1	as	as	ADP
flr-135	106	2	in	in	ADP
flr-135	106	3	logistic	logistic	ADJ
flr-135	106	4	regression	regression	NOUN
flr-135	106	5	,	,	PUNCT
flr-135	106	6	decision	decision	NOUN
flr-135	106	7	surfaces	surface	NOUN
flr-135	106	8	in	in	ADP
flr-135	106	9	the	the	DET
flr-135	106	10	neural	neural	ADJ
flr-135	106	11	networks	network	NOUN
flr-135	106	12	are	be	AUX
flr-135	106	13	hyperplanes	hyperplane	NOUN
flr-135	106	14	in	in	ADP
flr-135	106	15	the	the	DET
flr-135	106	16	input	input	NOUN
flr-135	106	17	space	space	NOUN
flr-135	106	18	.	.	PUNCT
flr-135	107	1	the	the	DET
flr-135	107	2	key	key	ADJ
flr-135	107	3	difference	difference	NOUN
flr-135	107	4	,	,	PUNCT
flr-135	107	5	though	though	ADV
flr-135	107	6	,	,	PUNCT
flr-135	107	7	between	between	ADP
flr-135	107	8	neural	neural	ADJ
flr-135	107	9	networks	network	NOUN
flr-135	107	10	and	and	CCONJ
flr-135	107	11	logistic	logistic	ADJ
flr-135	107	12	regression	regression	NOUN
flr-135	107	13	is	be	AUX
flr-135	107	14	that	that	SCONJ
flr-135	107	15	each	each	DET
flr-135	107	16	hidden	hide	VERB
flr-135	107	17	neuron	neuron	NOUN
flr-135	107	18	(	(	PUNCT
flr-135	107	19	other	other	ADJ
flr-135	107	20	than	than	ADP
flr-135	107	21	the	the	DET
flr-135	107	22	bias	bias	NOUN
flr-135	107	23	neuron	neuron	PROPN
flr-135	107	24	)	)	PUNCT
flr-135	107	25	produces	produce	VERB
flr-135	107	26	an	an	DET
flr-135	107	27	output	output	NOUN
flr-135	107	28	that	that	PRON
flr-135	107	29	corresponds	correspond	VERB
flr-135	107	30	to	to	ADP
flr-135	107	31	a	a	DET
flr-135	107	32	distinct	distinct	ADJ
flr-135	107	33	,	,	PUNCT
flr-135	107	34	discriminating	discriminate	VERB
flr-135	107	35	hyperplane	hyperplane	NOUN
flr-135	107	36	in	in	ADP
flr-135	107	37	the	the	DET
flr-135	107	38	input	input	NOUN
flr-135	107	39	space	space	NOUN
flr-135	107	40	.	.	PUNCT
flr-135	108	1	when	when	SCONJ
flr-135	108	2	these	these	PRON
flr-135	108	3	are	be	AUX
flr-135	108	4	weighted	weight	VERB
flr-135	108	5	,	,	PUNCT
flr-135	108	6	summed	sum	VERB
flr-135	108	7	,	,	PUNCT
flr-135	108	8	and	and	CCONJ
flr-135	108	9	transformed	transform	VERB
flr-135	108	10	at	at	ADP
flr-135	108	11	an	an	DET
flr-135	108	12	output	output	NOUN
flr-135	108	13	neuron	neuron	NOUN
flr-135	108	14	,	,	PUNCT
flr-135	108	15	the	the	DET
flr-135	108	16	resulting	result	VERB
flr-135	108	17	output	output	NOUN
flr-135	108	18	corresponds	correspond	VERB
flr-135	108	19	very	very	ADV
flr-135	108	20	closely	closely	ADV
flr-135	108	21	to	to	ADP
flr-135	108	22	a	a	DET
flr-135	108	23	multidimensional	multidimensional	ADJ
flr-135	108	24	step	step	NOUN
flr-135	108	25	function	function	NOUN
flr-135	108	26	.	.	PUNCT
flr-135	109	1	it	it	PRON
flr-135	109	2	is	be	AUX
flr-135	109	3	found	find	VERB
flr-135	109	4	that	that	SCONJ
flr-135	109	5	the	the	DET
flr-135	109	6	boundaries	boundary	NOUN
flr-135	109	7	of	of	ADP
flr-135	109	8	regions	region	NOUN
flr-135	109	9	of	of	ADP
flr-135	109	10	similar	similar	ADJ
flr-135	109	11	probability	probability	NOUN
flr-135	109	12	are	be	AUX
flr-135	109	13	defined	define	VERB
flr-135	109	14	by	by	ADP
flr-135	109	15	the	the	DET
flr-135	109	16	discriminating	discriminate	VERB
flr-135	109	17	hyperplanes	hyperplane	NOUN
flr-135	109	18	,	,	PUNCT
flr-135	109	19	which	which	PRON
flr-135	109	20	crisscross	crisscross	VERB
flr-135	109	21	the	the	DET
flr-135	109	22	input	input	NOUN
flr-135	109	23	space	space	NOUN
flr-135	109	24	(	(	PUNCT
flr-135	109	25	dreiseitl	dreiseitl	VERB
flr-135	109	26	&	&	CCONJ
flr-135	109	27	ohnomachado	ohnomachado	PROPN
flr-135	109	28	,	,	PUNCT
flr-135	109	29	2002	2002	NUM
flr-135	109	30	)	)	PUNCT
flr-135	109	31	.	.	PUNCT
flr-135	110	1	given	give	VERB
flr-135	110	2	the	the	DET
flr-135	110	3	vast	vast	ADJ
flr-135	110	4	number	number	NOUN
flr-135	110	5	of	of	ADP
flr-135	110	6	practical	practical	ADJ
flr-135	110	7	applications	application	NOUN
flr-135	110	8	already	already	ADV
flr-135	110	9	mentioned	mention	VERB
flr-135	110	10	in	in	ADP
flr-135	110	11	the	the	DET
flr-135	110	12	original	original	ADJ
flr-135	110	13	article	article	NOUN
flr-135	110	14	by	by	ADP
flr-135	110	15	musso	musso	PROPN
flr-135	110	16	et	et	PROPN
flr-135	110	17	al	al	PROPN
flr-135	110	18	.	.	PROPN
flr-135	111	1	(	(	PUNCT
flr-135	111	2	2013	2013	NUM
flr-135	111	3	)	)	PUNCT
flr-135	111	4	,	,	PUNCT
flr-135	111	5	it	it	PRON
flr-135	111	6	is	be	AUX
flr-135	111	7	unfortunate	unfortunate	ADJ
flr-135	111	8	that	that	SCONJ
flr-135	111	9	edelsbrunner	edelsbrunner	NOUN
flr-135	111	10	and	and	CCONJ
flr-135	111	11	schneider	schneider	NOUN
flr-135	111	12	(	(	PUNCT
flr-135	111	13	2013	2013	NUM
flr-135	111	14	)	)	PUNCT
flr-135	111	15	choose	choose	VERB
flr-135	111	16	to	to	PART
flr-135	111	17	exemplify	exemplify	VERB
flr-135	111	18	an	an	DET
flr-135	111	19	unrealistic	unrealistic	ADJ
flr-135	111	20	example	example	NOUN
flr-135	111	21	of	of	ADP
flr-135	111	22	application	application	NOUN
flr-135	111	23	of	of	ADP
flr-135	111	24	anns	anns	NOUN
flr-135	111	25	in	in	ADP
flr-135	111	26	a	a	DET
flr-135	111	27	contrived	contrived	ADJ
flr-135	111	28	situation	situation	NOUN
flr-135	111	29	in	in	ADP
flr-135	111	30	which	which	PRON
flr-135	111	31	a	a	DET
flr-135	111	32	student	student	NOUN
flr-135	111	33	is	be	AUX
flr-135	111	34	eliminated	eliminate	VERB
flr-135	111	35	from	from	ADP
flr-135	111	36	a	a	DET
flr-135	111	37	programme	programme	NOUN
flr-135	111	38	based	base	VERB
flr-135	111	39	on	on	ADP
flr-135	111	40	a	a	DET
flr-135	111	41	neural	neural	ADJ
flr-135	111	42	network	network	NOUN
flr-135	111	43	classification	classification	NOUN
flr-135	111	44	.	.	PUNCT
flr-135	112	1	anns	ann	NOUN
flr-135	112	2	,	,	PUNCT
flr-135	112	3	like	like	ADP
flr-135	112	4	any	any	DET
flr-135	112	5	other	other	ADJ
flr-135	112	6	methodology	methodology	NOUN
flr-135	112	7	provides	provide	VERB
flr-135	112	8	the	the	DET
flr-135	112	9	researcher	researcher	NOUN
flr-135	112	10	or	or	CCONJ
flr-135	112	11	applied	apply	VERB
flr-135	112	12	scientist	scientist	NOUN
flr-135	112	13	with	with	ADP
flr-135	112	14	information	information	NOUN
flr-135	112	15	.	.	PUNCT
flr-135	113	1	as	as	SCONJ
flr-135	113	2	we	we	PRON
flr-135	113	3	have	have	AUX
flr-135	113	4	already	already	ADV
flr-135	113	5	shown	show	VERB
flr-135	113	6	from	from	ADP
flr-135	113	7	the	the	DET
flr-135	113	8	literature	literature	NOUN
flr-135	113	9	cited	cite	VERB
flr-135	113	10	,	,	PUNCT
flr-135	113	11	in	in	ADP
flr-135	113	12	the	the	DET
flr-135	113	13	case	case	NOUN
flr-135	113	14	of	of	ADP
flr-135	113	15	anns	ann	NOUN
flr-135	113	16	there	there	PRON
flr-135	113	17	are	be	VERB
flr-135	113	18	a	a	DET
flr-135	113	19	number	number	NOUN
flr-135	113	20	of	of	ADP
flr-135	113	21	methods	method	NOUN
flr-135	113	22	to	to	PART
flr-135	113	23	establish	establish	VERB
flr-135	113	24	the	the	DET
flr-135	113	25	necessary	necessary	ADJ
flr-135	113	26	input	input	NOUN
flr-135	113	27	-	-	PUNCT
flr-135	113	28	output	output	NOUN
flr-135	113	29	relationships	relationship	NOUN
flr-135	113	30	and	and	CCONJ
flr-135	113	31	to	to	PART
flr-135	113	32	determine	determine	VERB
flr-135	113	33	the	the	DET
flr-135	113	34	confidence	confidence	NOUN
flr-135	113	35	and	and	CCONJ
flr-135	113	36	prediction	prediction	NOUN
flr-135	113	37	intervals	interval	NOUN
flr-135	113	38	provided	provide	VERB
flr-135	113	39	by	by	ADP
flr-135	113	40	an	an	DET
flr-135	113	41	ann	ann	PROPN
flr-135	113	42	.	.	PUNCT
flr-135	114	1	therefore	therefore	ADV
flr-135	114	2	,	,	PUNCT
flr-135	114	3	the	the	DET
flr-135	114	4	contrived	contrived	ADJ
flr-135	114	5	diagnostic	diagnostic	ADJ
flr-135	114	6	example	example	NOUN
flr-135	114	7	provided	provide	VERB
flr-135	114	8	by	by	ADP
flr-135	114	9	edelsbrunner	edelsbrunner	NOUN
flr-135	114	10	and	and	CCONJ
flr-135	114	11	schneider	schneider	NOUN
flr-135	114	12	(	(	PUNCT
flr-135	114	13	2013	2013	NUM
flr-135	114	14	,	,	PUNCT
flr-135	114	15	pp	pp	ADJ
flr-135	114	16	.	.	NOUN
flr-135	114	17	100	100	NUM
flr-135	114	18	)	)	PUNCT
flr-135	114	19	shows	show	VERB
flr-135	114	20	an	an	DET
flr-135	114	21	underestimation	underestimation	NOUN
flr-135	114	22	/	/	SYM
flr-135	114	23	misinterpretation	misinterpretation	NOUN
flr-135	114	24	of	of	ADP
flr-135	114	25	the	the	DET
flr-135	114	26	potential	potential	NOUN
flr-135	114	27	of	of	ADP
flr-135	114	28	anns	ann	NOUN
flr-135	114	29	.	.	PUNCT
flr-135	115	1	furthermore	furthermore	ADV
flr-135	115	2	,	,	PUNCT
flr-135	115	3	poor	poor	ADJ
flr-135	115	4	advice	advice	NOUN
flr-135	115	5	is	be	AUX
flr-135	115	6	always	always	ADV
flr-135	115	7	a	a	DET
flr-135	115	8	problem	problem	NOUN
flr-135	115	9	,	,	PUNCT
flr-135	115	10	as	as	SCONJ
flr-135	115	11	would	would	AUX
flr-135	115	12	be	be	AUX
flr-135	115	13	the	the	DET
flr-135	115	14	case	case	NOUN
flr-135	115	15	in	in	ADP
flr-135	115	16	this	this	DET
flr-135	115	17	example	example	NOUN
flr-135	115	18	,	,	PUNCT
flr-135	115	19	with	with	ADP
flr-135	115	20	the	the	DET
flr-135	115	21	unfortunately	unfortunately	ADV
flr-135	115	22	frequent	frequent	ADJ
flr-135	115	23	decision	decision	NOUN
flr-135	115	24	-	-	PUNCT
flr-135	115	25	making	making	NOUN
flr-135	115	26	of	of	ADP
flr-135	115	27	students‟	students‟	DET
flr-135	115	28	career	career	NOUN
flr-135	115	29	paths	path	NOUN
flr-135	115	30	determined	determine	VERB
flr-135	115	31	by	by	ADP
flr-135	115	32	a	a	DET
flr-135	115	33	single	single	ADJ
flr-135	115	34	-	-	PUNCT
flr-135	115	35	point	point	NOUN
flr-135	115	36	examination	examination	NOUN
flr-135	115	37	.	.	PUNCT
flr-135	116	1	on	on	ADP
flr-135	116	2	the	the	DET
flr-135	116	3	other	other	ADJ
flr-135	116	4	hand	hand	NOUN
flr-135	116	5	,	,	PUNCT
flr-135	116	6	a	a	DET
flr-135	116	7	trusted	trust	VERB
flr-135	116	8	result	result	NOUN
flr-135	116	9	from	from	ADP
flr-135	116	10	a	a	PRON
flr-135	116	11	properly	properly	ADV
flr-135	116	12	constructed	construct	VERB
flr-135	116	13	and	and	CCONJ
flr-135	116	14	tested	test	VERB
flr-135	116	15	ann	ann	PROPN
flr-135	116	16	could	could	AUX
flr-135	116	17	provide	provide	VERB
flr-135	116	18	valuable	valuable	ADJ
flr-135	116	19	diagnostic	diagnostic	ADJ
flr-135	116	20	,	,	PUNCT
flr-135	116	21	educational	educational	ADJ
flr-135	116	22	,	,	PUNCT
flr-135	116	23	and	and	CCONJ
flr-135	116	24	public	public	ADJ
flr-135	116	25	policy	policy	NOUN
flr-135	116	26	information	information	NOUN
flr-135	116	27	.	.	PUNCT
flr-135	117	1	in	in	ADP
flr-135	117	2	fact	fact	NOUN
flr-135	117	3	,	,	PUNCT
flr-135	117	4	the	the	DET
flr-135	117	5	research	research	NOUN
flr-135	117	6	carried	carry	VERB
flr-135	117	7	out	out	ADP
flr-135	117	8	by	by	ADP
flr-135	117	9	some	some	PRON
flr-135	117	10	of	of	ADP
flr-135	117	11	these	these	DET
flr-135	117	12	authors	author	NOUN
flr-135	117	13	(	(	PUNCT
flr-135	117	14	cascallar	cascallar	ADJ
flr-135	117	15	et	et	PROPN
flr-135	117	16	al	al	PROPN
flr-135	117	17	.	.	PROPN
flr-135	117	18	,	,	PUNCT
flr-135	117	19	2006	2006	NUM
flr-135	117	20	;	;	PUNCT
flr-135	117	21	kyndt	kyndt	PROPN
flr-135	117	22	et	et	PROPN
flr-135	117	23	al	al	PROPN
flr-135	117	24	.	.	PROPN
flr-135	117	25	,	,	PUNCT
flr-135	117	26	2011	2011	NUM
flr-135	117	27	,	,	PUNCT
flr-135	117	28	2015	2015	NUM
flr-135	117	29	;	;	PUNCT
flr-135	117	30	luft	luft	PROPN
flr-135	117	31	,	,	PUNCT
flr-135	117	32	gomes	gome	NOUN
flr-135	117	33	,	,	PUNCT
flr-135	117	34	priori	priori	ADJ
flr-135	117	35	&	&	CCONJ
flr-135	117	36	takase	takase	NOUN
flr-135	117	37	,	,	PUNCT
flr-135	117	38	2013	2013	NUM
flr-135	117	39	;	;	PUNCT
flr-135	117	40	musso	musso	PROPN
flr-135	117	41	&	&	CCONJ
flr-135	117	42	cascallar	cascallar	ADJ
flr-135	117	43	,	,	PUNCT
flr-135	117	44	2009a	2009a	NUM
flr-135	117	45	;	;	PUNCT
flr-135	117	46	musso	musso	PROPN
flr-135	117	47	et	et	PROPN
flr-135	117	48	al	al	PROPN
flr-135	117	49	.	.	PROPN
flr-135	117	50	,	,	PUNCT
flr-135	117	51	2012	2012	NUM
flr-135	117	52	,	,	PUNCT
flr-135	117	53	2013	2013	NUM
flr-135	117	54	)	)	PUNCT
flr-135	117	55	provides	provide	VERB
flr-135	117	56	examples	example	NOUN
flr-135	117	57	of	of	ADP
flr-135	117	58	useful	useful	ADJ
flr-135	117	59	diagnostic	diagnostic	ADJ
flr-135	117	60	models	model	NOUN
flr-135	117	61	in	in	ADP
flr-135	117	62	the	the	DET
flr-135	117	63	educational	educational	ADJ
flr-135	117	64	field	field	NOUN
flr-135	117	65	.	.	PUNCT
flr-135	118	1	it	it	PRON
flr-135	118	2	is	be	AUX
flr-135	118	3	a	a	DET
flr-135	118	4	false	false	ADJ
flr-135	118	5	dichotomy	dichotomy	NOUN
flr-135	118	6	to	to	PART
flr-135	118	7	present	present	VERB
flr-135	118	8	modelling	modelling	NOUN
flr-135	118	9	for	for	ADP
flr-135	118	10	understanding	understanding	NOUN
flr-135	118	11	versus	versus	ADP
flr-135	118	12	modelling	modelling	NOUN
flr-135	118	13	for	for	ADP
flr-135	118	14	prediction	prediction	NOUN
flr-135	118	15	.	.	PUNCT
flr-135	119	1	in	in	ADP
flr-135	119	2	reality	reality	NOUN
flr-135	119	3	,	,	PUNCT
flr-135	119	4	both	both	PRON
flr-135	119	5	are	be	AUX
flr-135	119	6	achievable	achievable	ADJ
flr-135	119	7	and	and	CCONJ
flr-135	119	8	in	in	ADP
flr-135	119	9	fact	fact	NOUN
flr-135	119	10	they	they	PRON
flr-135	119	11	should	should	AUX
flr-135	119	12	be	be	AUX
flr-135	119	13	integrated	integrate	VERB
flr-135	119	14	for	for	ADP
flr-135	119	15	the	the	DET
flr-135	119	16	advancement	advancement	NOUN
flr-135	119	17	of	of	ADP
flr-135	119	18	the	the	DET
flr-135	119	19	field	field	NOUN
flr-135	119	20	and	and	CCONJ
flr-135	119	21	the	the	DET
flr-135	119	22	success	success	NOUN
flr-135	119	23	of	of	ADP
flr-135	119	24	each	each	DET
flr-135	119	25	application	application	NOUN
flr-135	119	26	.	.	PUNCT
flr-135	120	1	much	much	ADJ
flr-135	120	2	insight	insight	NOUN
flr-135	120	3	has	have	AUX
flr-135	120	4	been	be	AUX
flr-135	120	5	gained	gain	VERB
flr-135	120	6	by	by	ADP
flr-135	120	7	integrating	integrate	VERB
flr-135	120	8	understanding	understanding	NOUN
flr-135	120	9	with	with	ADP
flr-135	120	10	predictive	predictive	ADJ
flr-135	120	11	and	and	CCONJ
flr-135	120	12	classification	classification	NOUN
flr-135	120	13	models	model	NOUN
flr-135	120	14	.	.	PUNCT
flr-135	121	1	as	as	SCONJ
flr-135	121	2	is	be	AUX
flr-135	121	3	good	good	ADJ
flr-135	121	4	practice	practice	NOUN
flr-135	121	5	in	in	ADP
flr-135	121	6	various	various	ADJ
flr-135	121	7	fields	field	NOUN
flr-135	121	8	,	,	PUNCT
flr-135	121	9	especially	especially	ADV
flr-135	121	10	in	in	ADP
flr-135	121	11	applied	applied	ADJ
flr-135	121	12	statistics	statistic	NOUN
flr-135	121	13	and	and	CCONJ
flr-135	121	14	mathematical	mathematical	ADJ
flr-135	121	15	modelling	modelling	NOUN
flr-135	121	16	,	,	PUNCT
flr-135	121	17	the	the	DET
flr-135	121	18	various	various	ADJ
flr-135	121	19	approaches	approach	NOUN
flr-135	121	20	constitute	constitute	VERB
flr-135	121	21	a	a	DET
flr-135	121	22	toolbox	toolbox	NOUN
flr-135	121	23	that	that	PRON
flr-135	121	24	the	the	DET
flr-135	121	25	professional	professional	NOUN
flr-135	121	26	has	have	AUX
flr-135	121	27	available	available	ADJ
flr-135	121	28	in	in	ADP
flr-135	121	29	order	order	NOUN
flr-135	121	30	to	to	PART
flr-135	121	31	apply	apply	VERB
flr-135	121	32	the	the	DET
flr-135	121	33	best	good	ADJ
flr-135	121	34	method	method	NOUN
flr-135	121	35	for	for	ADP
flr-135	121	36	the	the	DET
flr-135	121	37	problem	problem	NOUN
flr-135	121	38	at	at	ADP
flr-135	121	39	hand	hand	NOUN
flr-135	121	40	.	.	PUNCT
flr-135	122	1	the	the	DET
flr-135	122	2	fact	fact	NOUN
flr-135	122	3	that	that	SCONJ
flr-135	122	4	our	our	PRON
flr-135	122	5	article	article	NOUN
flr-135	122	6	(	(	PUNCT
flr-135	122	7	musso	musso	PROPN
flr-135	122	8	et	et	PROPN
flr-135	122	9	al	al	PROPN
flr-135	122	10	.	.	PROPN
flr-135	122	11	,	,	PUNCT
flr-135	122	12	2013	2013	NUM
flr-135	122	13	)	)	PUNCT
flr-135	122	14	demonstrated	demonstrate	VERB
flr-135	122	15	the	the	DET
flr-135	122	16	use	use	NOUN
flr-135	122	17	of	of	ADP
flr-135	122	18	anns	anns	NOUN
flr-135	122	19	in	in	ADP
flr-135	122	20	a	a	DET
flr-135	122	21	given	give	VERB
flr-135	122	22	academic	academic	ADJ
flr-135	122	23	application	application	NOUN
flr-135	122	24	is	be	AUX
flr-135	122	25	not	not	PART
flr-135	122	26	meant	mean	VERB
flr-135	122	27	to	to	PART
flr-135	122	28	be	be	AUX
flr-135	122	29	exclusionary	exclusionary	ADJ
flr-135	122	30	.	.	PUNCT
flr-135	123	1	on	on	ADP
flr-135	123	2	the	the	DET
flr-135	123	3	contrary	contrary	NOUN
flr-135	123	4	,	,	PUNCT
flr-135	123	5	the	the	DET
flr-135	123	6	field	field	NOUN
flr-135	123	7	requires	require	VERB
flr-135	123	8	the	the	DET
flr-135	123	9	integration	integration	NOUN
flr-135	123	10	of	of	ADP
flr-135	123	11	mathematical	mathematical	ADJ
flr-135	123	12	modelling	modelling	NOUN
flr-135	123	13	and	and	CCONJ
flr-135	123	14	statistical	statistical	ADJ
flr-135	123	15	techniques	technique	NOUN
flr-135	123	16	.	.	PUNCT
flr-135	124	1	regarding	regard	VERB
flr-135	124	2	the	the	DET
flr-135	124	3	comments	comment	NOUN
flr-135	124	4	in	in	ADP
flr-135	124	5	nokelainen	nokelainen	NOUN
flr-135	124	6	and	and	CCONJ
flr-135	124	7	silander	silander	NOUN
flr-135	124	8	(	(	PUNCT
flr-135	124	9	2014	2014	NUM
flr-135	124	10	)	)	PUNCT
flr-135	124	11	on	on	ADP
flr-135	124	12	the	the	DET
flr-135	124	13	article	article	NOUN
flr-135	124	14	by	by	ADP
flr-135	124	15	musso	musso	PROPN
flr-135	124	16	et	et	PROPN
flr-135	124	17	al	al	PROPN
flr-135	124	18	.	.	PROPN
flr-135	125	1	(	(	PUNCT
flr-135	125	2	2013	2013	NUM
flr-135	125	3	)	)	PUNCT
flr-135	125	4	,	,	PUNCT
flr-135	125	5	they	they	PRON
flr-135	125	6	can	can	AUX
flr-135	125	7	be	be	AUX
flr-135	125	8	summarized	summarize	VERB
flr-135	125	9	in	in	ADP
flr-135	125	10	two	two	NUM
flr-135	125	11	main	main	ADJ
flr-135	125	12	points	point	NOUN
flr-135	125	13	.	.	PUNCT
flr-135	126	1	the	the	DET
flr-135	126	2	first	first	ADJ
flr-135	126	3	point	point	NOUN
flr-135	126	4	questions	question	NOUN
flr-135	126	5	whether	whether	SCONJ
flr-135	126	6	the	the	DET
flr-135	126	7	methodology	methodology	NOUN
flr-135	126	8	used	use	VERB
flr-135	126	9	was	be	AUX
flr-135	126	10	rigorous	rigorous	ADJ
flr-135	126	11	in	in	ADP
flr-135	126	12	its	its	PRON
flr-135	126	13	procedures	procedure	NOUN
flr-135	126	14	,	,	PUNCT
flr-135	126	15	and	and	CCONJ
flr-135	126	16	the	the	DET
flr-135	126	17	second	second	ADJ
flr-135	126	18	suggests	suggest	VERB
flr-135	126	19	comparing	compare	VERB
flr-135	126	20	the	the	DET
flr-135	126	21	neural	neural	ADJ
flr-135	126	22	cascallar	cascallar	NOUN
flr-135	127	1	et	et	PROPN
flr-135	127	2	al	al	PROPN
flr-135	127	3	74	74	NUM
flr-135	128	1	|	|	ADV
flr-135	128	2	f	f	NOUN
flr-135	128	3	l	l	NOUN
flr-135	128	4	r	r	NOUN
flr-135	128	5	network	network	NOUN
flr-135	128	6	results	result	VERB
flr-135	128	7	with	with	ADP
flr-135	128	8	those	those	PRON
flr-135	128	9	obtained	obtain	VERB
flr-135	128	10	from	from	ADP
flr-135	128	11	another	another	DET
flr-135	128	12	discriminative	discriminative	NOUN
flr-135	128	13	classifier	classifier	NOUN
flr-135	128	14	in	in	ADP
flr-135	128	15	addition	addition	NOUN
flr-135	128	16	to	to	ADP
flr-135	128	17	the	the	DET
flr-135	128	18	comparison	comparison	NOUN
flr-135	128	19	to	to	ADP
flr-135	128	20	a	a	DET
flr-135	128	21	generative	generative	ADJ
flr-135	128	22	classifier	classifier	NOUN
flr-135	128	23	such	such	ADJ
flr-135	128	24	as	as	ADP
flr-135	128	25	discriminant	discriminant	ADJ
flr-135	128	26	analysis	analysis	NOUN
flr-135	128	27	.	.	PUNCT
flr-135	129	1	it	it	PRON
flr-135	129	2	is	be	AUX
flr-135	129	3	very	very	ADV
flr-135	129	4	important	important	ADJ
flr-135	129	5	to	to	PART
flr-135	129	6	clarify	clarify	VERB
flr-135	129	7	that	that	SCONJ
flr-135	129	8	the	the	DET
flr-135	129	9	data	datum	NOUN
flr-135	129	10	reported	report	VERB
flr-135	129	11	in	in	ADP
flr-135	129	12	musso	musso	PROPN
flr-135	129	13	et	et	PROPN
flr-135	129	14	al	al	PROPN
flr-135	129	15	.	.	PROPN
flr-135	130	1	(	(	PUNCT
flr-135	130	2	2013	2013	NUM
flr-135	130	3	)	)	PUNCT
flr-135	130	4	rigorously	rigorously	ADV
flr-135	130	5	followed	follow	VERB
flr-135	130	6	the	the	DET
flr-135	130	7	standards	standard	NOUN
flr-135	130	8	established	establish	VERB
flr-135	130	9	by	by	ADP
flr-135	130	10	the	the	DET
flr-135	130	11	message	message	NOUN
flr-135	130	12	understanding	understand	VERB
flr-135	130	13	conferences	conference	NOUN
flr-135	130	14	(	(	PUNCT
flr-135	130	15	muc	muc	X
flr-135	130	16	)	)	PUNCT
flr-135	130	17	(	(	PUNCT
flr-135	130	18	grishman	grishman	PROPN
flr-135	130	19	&	&	CCONJ
flr-135	130	20	sundheim	sundheim	PROPN
flr-135	130	21	(	(	PUNCT
flr-135	130	22	1996	1996	NUM
flr-135	130	23	)	)	PUNCT
flr-135	130	24	.	.	PUNCT
flr-135	131	1	as	as	SCONJ
flr-135	131	2	is	be	AUX
flr-135	131	3	clearly	clearly	ADV
flr-135	131	4	stated	state	VERB
flr-135	131	5	in	in	ADP
flr-135	131	6	the	the	DET
flr-135	131	7	musso	musso	PROPN
flr-135	131	8	et	et	PROPN
flr-135	131	9	al	al	PROPN
flr-135	131	10	.	.	PROPN
flr-135	132	1	(	(	PUNCT
flr-135	132	2	2013	2013	NUM
flr-135	132	3	)	)	PUNCT
flr-135	132	4	article	article	NOUN
flr-135	132	5	,	,	PUNCT
flr-135	132	6	“	"	PUNCT
flr-135	132	7	the	the	DET
flr-135	132	8	training	training	NOUN
flr-135	132	9	and	and	CCONJ
flr-135	132	10	testing	testing	NOUN
flr-135	132	11	samples	sample	NOUN
flr-135	132	12	were	be	AUX
flr-135	132	13	selected	select	VERB
flr-135	132	14	at	at	ADP
flr-135	132	15	random	random	ADJ
flr-135	132	16	from	from	ADP
flr-135	132	17	the	the	DET
flr-135	132	18	existing	exist	VERB
flr-135	132	19	data	datum	NOUN
flr-135	132	20	and	and	CCONJ
flr-135	132	21	the	the	DET
flr-135	132	22	proportions	proportion	NOUN
flr-135	132	23	were	be	AUX
flr-135	132	24	adjusted	adjust	VERB
flr-135	132	25	in	in	ADP
flr-135	132	26	order	order	NOUN
flr-135	132	27	to	to	PART
flr-135	132	28	maximize	maximize	VERB
flr-135	132	29	the	the	DET
flr-135	132	30	training	training	NOUN
flr-135	132	31	sample	sample	NOUN
flr-135	132	32	while	while	SCONJ
flr-135	132	33	preserving	preserve	VERB
flr-135	132	34	the	the	DET
flr-135	132	35	appearance	appearance	NOUN
flr-135	132	36	of	of	ADP
flr-135	132	37	all	all	DET
flr-135	132	38	detected	detect	VERB
flr-135	132	39	patterns	pattern	NOUN
flr-135	132	40	in	in	ADP
flr-135	132	41	the	the	DET
flr-135	132	42	testing	testing	NOUN
flr-135	132	43	sample	sample	NOUN
flr-135	132	44	,	,	PUNCT
flr-135	132	45	so	so	SCONJ
flr-135	132	46	as	as	SCONJ
flr-135	132	47	to	to	PART
flr-135	132	48	be	be	AUX
flr-135	132	49	able	able	ADJ
flr-135	132	50	to	to	PART
flr-135	132	51	appropriately	appropriately	ADV
flr-135	132	52	test	test	VERB
flr-135	132	53	the	the	DET
flr-135	132	54	model	model	NOUN
flr-135	132	55	”	"	PUNCT
flr-135	132	56	(	(	PUNCT
flr-135	132	57	p.	p.	NOUN
flr-135	132	58	60	60	NUM
flr-135	132	59	)	)	PUNCT
flr-135	132	60	.	.	PUNCT
flr-135	133	1	the	the	DET
flr-135	133	2	two	two	NUM
flr-135	133	3	samples	sample	NOUN
flr-135	133	4	were	be	AUX
flr-135	133	5	chosen	choose	VERB
flr-135	133	6	at	at	ADP
flr-135	133	7	random	random	ADJ
flr-135	133	8	,	,	PUNCT
flr-135	133	9	precisely	precisely	ADV
flr-135	133	10	to	to	PART
flr-135	133	11	avoid	avoid	VERB
flr-135	133	12	what	what	PRON
flr-135	133	13	nokelainen	nokelainen	NOUN
flr-135	133	14	and	and	CCONJ
flr-135	133	15	silander	silander	NOUN
flr-135	133	16	(	(	PUNCT
flr-135	133	17	2014	2014	NUM
flr-135	133	18	)	)	PUNCT
flr-135	133	19	put	put	VERB
flr-135	133	20	forward	forward	ADV
flr-135	133	21	.	.	PUNCT
flr-135	134	1	these	these	DET
flr-135	134	2	authors	author	NOUN
flr-135	134	3	seem	seem	VERB
flr-135	134	4	to	to	PART
flr-135	134	5	have	have	AUX
flr-135	134	6	misinterpreted	misinterpret	VERB
flr-135	134	7	the	the	DET
flr-135	134	8	sections	section	NOUN
flr-135	134	9	on	on	ADP
flr-135	134	10	analyses	analysis	NOUN
flr-135	134	11	procedures	procedure	NOUN
flr-135	134	12	and	and	CCONJ
flr-135	134	13	architecture	architecture	NOUN
flr-135	134	14	of	of	ADP
flr-135	134	15	the	the	DET
flr-135	134	16	neural	neural	ADJ
flr-135	134	17	network	network	NOUN
flr-135	134	18	(	(	PUNCT
flr-135	134	19	musso	musso	PROPN
flr-135	134	20	et	et	PROPN
flr-135	134	21	al	al	PROPN
flr-135	134	22	.	.	PROPN
flr-135	134	23	,	,	PUNCT
flr-135	134	24	2013	2013	NUM
flr-135	134	25	,	,	PUNCT
flr-135	134	26	pp	pp	ADJ
flr-135	134	27	.	.	PUNCT
flr-135	135	1	52	52	NUM
flr-135	135	2	-	-	SYM
flr-135	135	3	54	54	NUM
flr-135	135	4	)	)	PUNCT
flr-135	135	5	in	in	ADP
flr-135	135	6	which	which	PRON
flr-135	135	7	the	the	DET
flr-135	135	8	process	process	NOUN
flr-135	135	9	is	be	AUX
flr-135	135	10	described	describe	VERB
flr-135	135	11	in	in	ADP
flr-135	135	12	detail	detail	NOUN
flr-135	135	13	,	,	PUNCT
flr-135	135	14	and	and	CCONJ
flr-135	135	15	they	they	PRON
flr-135	135	16	completely	completely	ADV
flr-135	135	17	misjudge	misjudge	VERB
flr-135	135	18	when	when	SCONJ
flr-135	135	19	they	they	PRON
flr-135	135	20	state	state	VERB
flr-135	135	21	that	that	SCONJ
flr-135	135	22	“	"	PUNCT
flr-135	135	23	the	the	DET
flr-135	135	24	paper	paper	NOUN
flr-135	135	25	by	by	ADP
flr-135	135	26	musso	musso	PROPN
flr-135	135	27	and	and	CCONJ
flr-135	135	28	her	her	PRON
flr-135	135	29	colleagues	colleague	NOUN
flr-135	135	30	(	(	PUNCT
flr-135	135	31	2013	2013	NUM
flr-135	135	32	)	)	PUNCT
flr-135	135	33	practically	practically	ADV
flr-135	135	34	acknowledges	acknowledge	VERB
flr-135	135	35	that	that	SCONJ
flr-135	135	36	such	such	DET
flr-135	135	37	a	a	DET
flr-135	135	38	discipline	discipline	NOUN
flr-135	135	39	was	be	AUX
flr-135	135	40	not	not	PART
flr-135	135	41	rigorously	rigorously	ADV
flr-135	135	42	followed	follow	VERB
flr-135	135	43	.	.	PUNCT
flr-135	135	44	”	"	PUNCT
flr-135	136	1	(	(	PUNCT
flr-135	136	2	nokelainen	nokelainen	NOUN
flr-135	136	3	&	&	CCONJ
flr-135	136	4	silander	silander	NOUN
flr-135	136	5	,	,	PUNCT
flr-135	136	6	2014	2014	NUM
flr-135	136	7	,	,	PUNCT
flr-135	136	8	p.	p.	NOUN
flr-135	136	9	79	79	NUM
flr-135	136	10	)	)	PUNCT
flr-135	136	11	.	.	PUNCT
flr-135	137	1	it	it	PRON
flr-135	137	2	is	be	AUX
flr-135	137	3	clearly	clearly	ADV
flr-135	137	4	stated	state	VERB
flr-135	137	5	in	in	ADP
flr-135	137	6	the	the	DET
flr-135	137	7	above	above	ADV
flr-135	137	8	mentioned	mention	VERB
flr-135	137	9	sections	section	NOUN
flr-135	137	10	the	the	DET
flr-135	137	11	way	way	NOUN
flr-135	137	12	in	in	ADP
flr-135	137	13	which	which	PRON
flr-135	137	14	the	the	DET
flr-135	137	15	sample	sample	NOUN
flr-135	137	16	was	be	AUX
flr-135	137	17	divided	divide	VERB
flr-135	137	18	,	,	PUNCT
flr-135	137	19	the	the	DET
flr-135	137	20	complete	complete	ADJ
flr-135	137	21	independence	independence	NOUN
flr-135	137	22	of	of	ADP
flr-135	137	23	the	the	DET
flr-135	137	24	randomly	randomly	ADV
flr-135	137	25	selected	select	VERB
flr-135	137	26	training	training	NOUN
flr-135	137	27	and	and	CCONJ
flr-135	137	28	testing	testing	NOUN
flr-135	137	29	subsets	subset	NOUN
flr-135	137	30	,	,	PUNCT
flr-135	137	31	and	and	CCONJ
flr-135	137	32	the	the	DET
flr-135	137	33	criteria	criterion	NOUN
flr-135	137	34	followed	follow	VERB
flr-135	137	35	to	to	PART
flr-135	137	36	determine	determine	VERB
flr-135	137	37	the	the	DET
flr-135	137	38	proportions	proportion	NOUN
flr-135	137	39	of	of	ADP
flr-135	137	40	cases	case	NOUN
flr-135	137	41	in	in	ADP
flr-135	137	42	each	each	PRON
flr-135	137	43	of	of	ADP
flr-135	137	44	the	the	DET
flr-135	137	45	two	two	NUM
flr-135	137	46	subsets	subset	NOUN
flr-135	137	47	.	.	PUNCT
flr-135	138	1	ironically	ironically	ADV
flr-135	138	2	,	,	PUNCT
flr-135	138	3	the	the	DET
flr-135	138	4	procedures	procedure	NOUN
flr-135	138	5	followed	follow	VERB
flr-135	138	6	coincide	coincide	NOUN
flr-135	138	7	with	with	ADP
flr-135	138	8	those	those	PRON
flr-135	138	9	suggested	suggest	VERB
flr-135	138	10	by	by	ADP
flr-135	138	11	(	(	PUNCT
flr-135	138	12	nokelainen	nokelainen	NOUN
flr-135	138	13	&	&	CCONJ
flr-135	138	14	silander	silander	NOUN
flr-135	138	15	,	,	PUNCT
flr-135	138	16	2014	2014	NUM
flr-135	138	17	,	,	PUNCT
flr-135	138	18	p.	p.	NOUN
flr-135	138	19	79	79	NUM
flr-135	138	20	)	)	PUNCT
flr-135	138	21	.	.	PUNCT
flr-135	139	1	let	let	VERB
flr-135	139	2	us	we	PRON
flr-135	139	3	state	state	VERB
flr-135	139	4	unequivocally	unequivocally	ADV
flr-135	139	5	that	that	SCONJ
flr-135	139	6	both	both	DET
flr-135	139	7	subsets	subset	NOUN
flr-135	139	8	of	of	ADP
flr-135	139	9	cases	case	NOUN
flr-135	139	10	in	in	ADP
flr-135	139	11	the	the	DET
flr-135	139	12	training	training	NOUN
flr-135	139	13	and	and	CCONJ
flr-135	139	14	testing	testing	NOUN
flr-135	139	15	samples	sample	NOUN
flr-135	139	16	were	be	AUX
flr-135	139	17	analyzed	analyze	VERB
flr-135	139	18	separately	separately	ADV
flr-135	139	19	.	.	PUNCT
flr-135	140	1	in	in	ADP
flr-135	140	2	addition	addition	NOUN
flr-135	140	3	,	,	PUNCT
flr-135	140	4	all	all	DET
flr-135	140	5	training	training	NOUN
flr-135	140	6	of	of	ADP
flr-135	140	7	the	the	DET
flr-135	140	8	neural	neural	ADJ
flr-135	140	9	network	network	NOUN
flr-135	140	10	model	model	NOUN
flr-135	140	11	was	be	AUX
flr-135	140	12	carried	carry	VERB
flr-135	140	13	out	out	ADP
flr-135	140	14	on	on	ADP
flr-135	140	15	the	the	DET
flr-135	140	16	training	training	NOUN
flr-135	140	17	sample	sample	NOUN
flr-135	140	18	,	,	PUNCT
flr-135	140	19	as	as	ADV
flr-135	140	20	well	well	ADV
flr-135	140	21	as	as	ADP
flr-135	140	22	all	all	DET
flr-135	140	23	parameter	parameter	NOUN
flr-135	140	24	adjustments	adjustment	NOUN
flr-135	140	25	,	,	PUNCT
flr-135	140	26	until	until	SCONJ
flr-135	140	27	the	the	DET
flr-135	140	28	desired	desire	VERB
flr-135	140	29	level	level	NOUN
flr-135	140	30	of	of	ADP
flr-135	140	31	precision	precision	NOUN
flr-135	140	32	was	be	AUX
flr-135	140	33	attained	attain	VERB
flr-135	140	34	.	.	PUNCT
flr-135	141	1	then	then	ADV
flr-135	141	2	,	,	PUNCT
flr-135	141	3	the	the	DET
flr-135	141	4	model	model	NOUN
flr-135	141	5	was	be	AUX
flr-135	141	6	independently	independently	ADV
flr-135	141	7	tested	test	VERB
flr-135	141	8	on	on	ADP
flr-135	141	9	the	the	DET
flr-135	141	10	testing	testing	NOUN
flr-135	141	11	sample	sample	NOUN
flr-135	141	12	,	,	PUNCT
flr-135	141	13	capturing	capture	VERB
flr-135	141	14	the	the	DET
flr-135	141	15	generalization	generalization	NOUN
flr-135	141	16	of	of	ADP
flr-135	141	17	the	the	DET
flr-135	141	18	network	network	NOUN
flr-135	141	19	structure	structure	NOUN
flr-135	141	20	and	and	CCONJ
flr-135	141	21	the	the	DET
flr-135	141	22	learning	learning	NOUN
flr-135	141	23	parameters	parameter	NOUN
flr-135	141	24	.	.	PUNCT
flr-135	142	1	none	none	NOUN
flr-135	142	2	of	of	ADP
flr-135	142	3	the	the	DET
flr-135	142	4	model	model	NOUN
flr-135	142	5	building	building	NOUN
flr-135	142	6	took	take	VERB
flr-135	142	7	place	place	NOUN
flr-135	142	8	on	on	ADP
flr-135	142	9	the	the	DET
flr-135	142	10	testing	testing	NOUN
flr-135	142	11	sample	sample	NOUN
flr-135	142	12	as	as	ADP
flr-135	142	13	nokelainen	nokelainen	NOUN
flr-135	142	14	and	and	CCONJ
flr-135	142	15	silander	silander	NOUN
flr-135	142	16	(	(	PUNCT
flr-135	142	17	2014	2014	NUM
flr-135	142	18	)	)	PUNCT
flr-135	142	19	incorrectly	incorrectly	ADV
flr-135	142	20	assume	assume	VERB
flr-135	142	21	.	.	PUNCT
flr-135	143	1	thus	thus	ADV
flr-135	143	2	,	,	PUNCT
flr-135	143	3	the	the	DET
flr-135	143	4	performance	performance	NOUN
flr-135	143	5	of	of	ADP
flr-135	143	6	the	the	DET
flr-135	143	7	model	model	NOUN
flr-135	143	8	with	with	ADP
flr-135	143	9	the	the	DET
flr-135	143	10	testing	testing	NOUN
flr-135	143	11	subset	subset	NOUN
flr-135	143	12	actually	actually	ADV
flr-135	143	13	provides	provide	VERB
flr-135	143	14	an	an	DET
flr-135	143	15	indication	indication	NOUN
flr-135	143	16	of	of	ADP
flr-135	143	17	the	the	DET
flr-135	143	18	generalization	generalization	NOUN
flr-135	143	19	of	of	ADP
flr-135	143	20	the	the	DET
flr-135	143	21	model	model	NOUN
flr-135	143	22	,	,	PUNCT
flr-135	143	23	not	not	PART
flr-135	143	24	just	just	ADV
flr-135	143	25	“	"	PUNCT
flr-135	143	26	fit	fit	ADJ
flr-135	143	27	”	"	PUNCT
flr-135	143	28	as	as	ADP
flr-135	143	29	nokelainen	nokelainen	NOUN
flr-135	143	30	and	and	CCONJ
flr-135	143	31	silander	silander	NOUN
flr-135	143	32	(	(	PUNCT
flr-135	143	33	2014	2014	NUM
flr-135	143	34	,	,	PUNCT
flr-135	143	35	pp	pp	ADJ
flr-135	143	36	.	.	PUNCT
flr-135	143	37	79	79	NUM
flr-135	143	38	)	)	PUNCT
flr-135	143	39	also	also	ADV
flr-135	143	40	incorrectly	incorrectly	ADV
flr-135	143	41	state	state	NOUN
flr-135	143	42	.	.	PUNCT
flr-135	144	1	a	a	DET
flr-135	144	2	related	related	ADJ
flr-135	144	3	comment	comment	NOUN
flr-135	144	4	regarding	regard	VERB
flr-135	144	5	the	the	DET
flr-135	144	6	“	"	PUNCT
flr-135	144	7	ethical	ethical	ADJ
flr-135	144	8	standards	standard	NOUN
flr-135	144	9	”	"	PUNCT
flr-135	144	10	of	of	ADP
flr-135	144	11	the	the	DET
flr-135	144	12	musso	musso	PROPN
flr-135	144	13	et	et	PROPN
flr-135	144	14	al	al	PROPN
flr-135	144	15	.	.	PROPN
flr-135	145	1	(	(	PUNCT
flr-135	145	2	2013	2013	NUM
flr-135	145	3	)	)	PUNCT
flr-135	145	4	paper	paper	NOUN
flr-135	145	5	is	be	AUX
flr-135	145	6	truly	truly	ADV
flr-135	145	7	surprising	surprising	ADJ
flr-135	145	8	.	.	PUNCT
flr-135	146	1	do	do	AUX
flr-135	146	2	nokelainen	nokelainen	VERB
flr-135	146	3	and	and	CCONJ
flr-135	146	4	silander	silander	NOUN
flr-135	146	5	(	(	PUNCT
flr-135	146	6	2014	2014	NUM
flr-135	146	7	)	)	PUNCT
flr-135	146	8	truly	truly	ADV
flr-135	146	9	believe	believe	VERB
flr-135	146	10	or	or	CCONJ
flr-135	146	11	imply	imply	VERB
flr-135	146	12	that	that	SCONJ
flr-135	146	13	the	the	DET
flr-135	146	14	authors	author	NOUN
flr-135	146	15	could	could	AUX
flr-135	146	16	not	not	PART
flr-135	146	17	“	"	PUNCT
flr-135	146	18	refrain	refrain	VERB
flr-135	146	19	from	from	ADP
flr-135	146	20	cheating	cheat	VERB
flr-135	146	21	(	(	PUNCT
flr-135	146	22	using	use	VERB
flr-135	146	23	the	the	DET
flr-135	146	24	test	test	NOUN
flr-135	146	25	data	datum	NOUN
flr-135	146	26	)	)	PUNCT
flr-135	146	27	”	"	PUNCT
flr-135	147	1	(	(	PUNCT
flr-135	147	2	nokelainen	nokelainen	NOUN
flr-135	147	3	&	&	CCONJ
flr-135	147	4	silander	silander	PROPN
flr-135	147	5	(	(	PUNCT
flr-135	147	6	2014	2014	NUM
flr-135	147	7	,	,	PUNCT
flr-135	147	8	p.	p.	NOUN
flr-135	147	9	79	79	NUM
flr-135	147	10	)	)	PUNCT
flr-135	147	11	in	in	ADP
flr-135	147	12	developing	develop	VERB
flr-135	147	13	the	the	DET
flr-135	147	14	model	model	NOUN
flr-135	147	15	?	?	PUNCT
flr-135	148	1	if	if	SCONJ
flr-135	148	2	so	so	ADV
flr-135	148	3	,	,	PUNCT
flr-135	148	4	it	it	PRON
flr-135	148	5	is	be	AUX
flr-135	148	6	alarming	alarming	ADJ
flr-135	148	7	,	,	PUNCT
flr-135	148	8	because	because	SCONJ
flr-135	148	9	they	they	PRON
flr-135	148	10	are	be	AUX
flr-135	148	11	making	make	VERB
flr-135	148	12	a	a	DET
flr-135	148	13	serious	serious	ADJ
flr-135	148	14	assumption	assumption	NOUN
flr-135	148	15	regarding	regard	VERB
flr-135	148	16	the	the	DET
flr-135	148	17	authors	author	NOUN
flr-135	148	18	or	or	CCONJ
flr-135	148	19	at	at	ADP
flr-135	148	20	best	good	ADJ
flr-135	148	21	an	an	DET
flr-135	148	22	implication	implication	NOUN
flr-135	148	23	of	of	ADP
flr-135	148	24	ignorance	ignorance	NOUN
flr-135	148	25	of	of	ADP
flr-135	148	26	basic	basic	ADJ
flr-135	148	27	rules	rule	NOUN
flr-135	148	28	of	of	ADP
flr-135	148	29	science	science	NOUN
flr-135	148	30	and	and	CCONJ
flr-135	148	31	of	of	ADP
flr-135	148	32	this	this	DET
flr-135	148	33	methodology	methodology	NOUN
flr-135	148	34	in	in	ADP
flr-135	148	35	particular	particular	ADJ
flr-135	148	36	.	.	PUNCT
flr-135	149	1	their	their	PRON
flr-135	149	2	fear	fear	NOUN
flr-135	149	3	of	of	ADP
flr-135	149	4	“	"	PUNCT
flr-135	149	5	cheating	cheat	VERB
flr-135	149	6	”	"	PUNCT
flr-135	149	7	and	and	CCONJ
flr-135	149	8	their	their	PRON
flr-135	149	9	implication	implication	NOUN
flr-135	149	10	that	that	SCONJ
flr-135	149	11	the	the	DET
flr-135	149	12	testing	testing	NOUN
flr-135	149	13	sample	sample	NOUN
flr-135	149	14	analysis	analysis	NOUN
flr-135	149	15	should	should	AUX
flr-135	149	16	be	be	AUX
flr-135	149	17	carried	carry	VERB
flr-135	149	18	out	out	ADP
flr-135	149	19	by	by	ADP
flr-135	149	20	different	different	ADJ
flr-135	149	21	researchers	researcher	NOUN
flr-135	149	22	because	because	SCONJ
flr-135	149	23	of	of	ADP
flr-135	149	24	this	this	DET
flr-135	149	25	assumed	assume	VERB
flr-135	149	26	temptation	temptation	NOUN
flr-135	149	27	to	to	PART
flr-135	149	28	cheat	cheat	VERB
flr-135	149	29	could	could	AUX
flr-135	149	30	be	be	AUX
flr-135	149	31	extended	extend	VERB
flr-135	149	32	to	to	ADP
flr-135	149	33	all	all	DET
flr-135	149	34	research	research	NOUN
flr-135	149	35	in	in	ADP
flr-135	149	36	all	all	DET
flr-135	149	37	areas	area	NOUN
flr-135	149	38	and	and	CCONJ
flr-135	149	39	all	all	DET
flr-135	149	40	statistical	statistical	ADJ
flr-135	149	41	methods	method	NOUN
flr-135	149	42	.	.	PUNCT
flr-135	150	1	it	it	PRON
flr-135	150	2	is	be	AUX
flr-135	150	3	precisely	precisely	ADV
flr-135	150	4	part	part	NOUN
flr-135	150	5	of	of	ADP
flr-135	150	6	the	the	DET
flr-135	150	7	scientific	scientific	ADJ
flr-135	150	8	method	method	NOUN
flr-135	150	9	to	to	PART
flr-135	150	10	follow	follow	VERB
flr-135	150	11	any	any	DET
flr-135	150	12	scientific	scientific	ADJ
flr-135	150	13	finding	finding	NOUN
flr-135	150	14	with	with	ADP
flr-135	150	15	careful	careful	ADJ
flr-135	150	16	replications	replication	NOUN
flr-135	150	17	,	,	PUNCT
flr-135	150	18	not	not	PART
flr-135	150	19	simply	simply	ADV
flr-135	150	20	to	to	PART
flr-135	150	21	avoid	avoid	VERB
flr-135	150	22	cheating	cheat	VERB
flr-135	150	23	,	,	PUNCT
flr-135	150	24	but	but	CCONJ
flr-135	150	25	to	to	PART
flr-135	150	26	truly	truly	ADV
flr-135	150	27	evaluate	evaluate	VERB
flr-135	150	28	the	the	DET
flr-135	150	29	generalizability	generalizability	NOUN
flr-135	150	30	of	of	ADP
flr-135	150	31	scientific	scientific	ADJ
flr-135	150	32	results	result	NOUN
flr-135	150	33	.	.	PUNCT
flr-135	151	1	it	it	PRON
flr-135	151	2	does	do	AUX
flr-135	151	3	not	not	PART
flr-135	151	4	mean	mean	VERB
flr-135	151	5	that	that	SCONJ
flr-135	151	6	we	we	PRON
flr-135	151	7	can	can	AUX
flr-135	151	8	not	not	PART
flr-135	151	9	trust	trust	VERB
flr-135	151	10	researchers	researcher	NOUN
flr-135	151	11	,	,	PUNCT
flr-135	151	12	at	at	ADP
flr-135	151	13	least	least	ADJ
flr-135	151	14	a	a	PRON
flr-135	151	15	priori	priori	ADV
flr-135	151	16	,	,	PUNCT
flr-135	151	17	with	with	ADP
flr-135	151	18	carrying	carry	VERB
flr-135	151	19	out	out	ADP
flr-135	151	20	an	an	DET
flr-135	151	21	ethically	ethically	ADV
flr-135	151	22	sound	sound	ADJ
flr-135	151	23	analysis	analysis	NOUN
flr-135	151	24	.	.	PUNCT
flr-135	152	1	if	if	SCONJ
flr-135	152	2	not	not	PART
flr-135	152	3	,	,	PUNCT
flr-135	152	4	all	all	DET
flr-135	152	5	findings	finding	NOUN
flr-135	152	6	,	,	PUNCT
flr-135	152	7	including	include	VERB
flr-135	152	8	theirs	theirs	PROPN
flr-135	152	9	,	,	PUNCT
flr-135	152	10	would	would	AUX
flr-135	152	11	be	be	AUX
flr-135	152	12	in	in	ADP
flr-135	152	13	question	question	NOUN
flr-135	152	14	.	.	PUNCT
flr-135	153	1	certainly	certainly	ADV
flr-135	153	2	,	,	PUNCT
flr-135	153	3	the	the	DET
flr-135	153	4	musso	musso	PROPN
flr-135	153	5	et	et	PROPN
flr-135	153	6	al	al	PROPN
flr-135	153	7	.	.	PROPN
flr-135	154	1	(	(	PUNCT
flr-135	154	2	2013	2013	NUM
flr-135	154	3	)	)	PUNCT
flr-135	154	4	article	article	NOUN
flr-135	154	5	followed	follow	VERB
flr-135	154	6	careful	careful	ADJ
flr-135	154	7	and	and	CCONJ
flr-135	154	8	rigorous	rigorous	ADJ
flr-135	154	9	methodological	methodological	ADJ
flr-135	154	10	procedures	procedure	NOUN
flr-135	154	11	.	.	PUNCT
flr-135	155	1	if	if	SCONJ
flr-135	155	2	their	their	PRON
flr-135	155	3	question	question	NOUN
flr-135	155	4	has	have	VERB
flr-135	155	5	to	to	PART
flr-135	155	6	do	do	VERB
flr-135	155	7	with	with	ADP
flr-135	155	8	the	the	DET
flr-135	155	9	perfect	perfect	ADJ
flr-135	155	10	classification	classification	NOUN
flr-135	155	11	obtained	obtain	VERB
flr-135	155	12	,	,	PUNCT
flr-135	155	13	it	it	PRON
flr-135	155	14	is	be	AUX
flr-135	155	15	the	the	DET
flr-135	155	16	product	product	NOUN
flr-135	155	17	both	both	PRON
flr-135	155	18	of	of	ADP
flr-135	155	19	the	the	DET
flr-135	155	20	appropriate	appropriate	ADJ
flr-135	155	21	modelling	modelling	NOUN
flr-135	155	22	process	process	NOUN
flr-135	155	23	carried	carry	VERB
flr-135	155	24	out	out	ADP
flr-135	155	25	,	,	PUNCT
flr-135	155	26	and	and	CCONJ
flr-135	155	27	of	of	ADP
flr-135	155	28	the	the	DET
flr-135	155	29	granularity	granularity	NOUN
flr-135	155	30	of	of	ADP
flr-135	155	31	the	the	DET
flr-135	155	32	expected	expect	VERB
flr-135	155	33	results	result	NOUN
flr-135	155	34	given	give	VERB
flr-135	155	35	the	the	DET
flr-135	155	36	available	available	ADJ
flr-135	155	37	data	datum	NOUN
flr-135	155	38	;	;	PUNCT
flr-135	155	39	it	it	PRON
flr-135	155	40	should	should	AUX
flr-135	155	41	be	be	AUX
flr-135	155	42	noted	note	VERB
flr-135	155	43	that	that	SCONJ
flr-135	155	44	the	the	DET
flr-135	155	45	correlation	correlation	NOUN
flr-135	155	46	between	between	ADP
flr-135	155	47	the	the	DET
flr-135	155	48	individual	individual	ADJ
flr-135	155	49	gpa	gpa	PROPN
flr-135	155	50	scores	score	NOUN
flr-135	155	51	of	of	ADP
flr-135	155	52	the	the	DET
flr-135	155	53	cascallar	cascallar	NOUN
flr-135	155	54	et	et	NOUN
flr-135	155	55	al	al	PROPN
flr-135	155	56	75	75	NUM
flr-135	156	1	|	|	ADV
flr-135	156	2	f	f	NOUN
flr-135	156	3	l	l	NOUN
flr-135	156	4	r	r	NOUN
flr-135	156	5	students	student	NOUN
flr-135	156	6	in	in	ADP
flr-135	156	7	the	the	DET
flr-135	156	8	whole	whole	ADJ
flr-135	156	9	testing	testing	NOUN
flr-135	156	10	sample	sample	NOUN
flr-135	156	11	and	and	CCONJ
flr-135	156	12	their	their	PRON
flr-135	156	13	predicted	predict	VERB
flr-135	156	14	score	score	NOUN
flr-135	156	15	(	(	PUNCT
flr-135	156	16	with	with	ADP
flr-135	156	17	data	datum	NOUN
flr-135	156	18	from	from	ADP
flr-135	156	19	one	one	NUM
flr-135	156	20	year	year	NOUN
flr-135	156	21	in	in	ADP
flr-135	156	22	advance	advance	NOUN
flr-135	156	23	)	)	PUNCT
flr-135	156	24	,	,	PUNCT
flr-135	156	25	was	be	AUX
flr-135	156	26	.86	.86	NUM
flr-135	156	27	(	(	PUNCT
flr-135	156	28	musso	musso	PROPN
flr-135	156	29	et	et	PROPN
flr-135	156	30	al	al	PROPN
flr-135	156	31	.	.	PROPN
flr-135	156	32	,	,	PUNCT
flr-135	156	33	2013	2013	NUM
flr-135	156	34	,	,	PUNCT
flr-135	156	35	p.	p.	NOUN
flr-135	156	36	64	64	NUM
flr-135	156	37	)	)	PUNCT
flr-135	156	38	.	.	PUNCT
flr-135	157	1	regarding	regard	VERB
flr-135	157	2	the	the	DET
flr-135	157	3	suggestion	suggestion	NOUN
flr-135	157	4	to	to	PART
flr-135	157	5	use	use	VERB
flr-135	157	6	other	other	ADJ
flr-135	157	7	discriminative	discriminative	NOUN
flr-135	157	8	classifiers	classifier	NOUN
flr-135	157	9	,	,	PUNCT
flr-135	157	10	such	such	ADJ
flr-135	157	11	as	as	ADP
flr-135	157	12	logistic	logistic	ADJ
flr-135	157	13	regression	regression	NOUN
flr-135	157	14	,	,	PUNCT
flr-135	157	15	to	to	PART
flr-135	157	16	compare	compare	VERB
flr-135	157	17	with	with	ADP
flr-135	157	18	the	the	DET
flr-135	157	19	results	result	NOUN
flr-135	157	20	obtained	obtain	VERB
flr-135	157	21	with	with	ADP
flr-135	157	22	the	the	DET
flr-135	157	23	neural	neural	ADJ
flr-135	157	24	network	network	NOUN
flr-135	157	25	model	model	NOUN
flr-135	157	26	,	,	PUNCT
flr-135	157	27	it	it	PRON
flr-135	157	28	is	be	AUX
flr-135	157	29	a	a	DET
flr-135	157	30	good	good	ADJ
flr-135	157	31	suggestion	suggestion	NOUN
flr-135	157	32	which	which	PRON
flr-135	157	33	has	have	AUX
flr-135	157	34	already	already	ADV
flr-135	157	35	been	be	AUX
flr-135	157	36	carried	carry	VERB
flr-135	157	37	out	out	ADP
flr-135	157	38	in	in	ADP
flr-135	157	39	the	the	DET
flr-135	157	40	literature	literature	NOUN
flr-135	157	41	(	(	PUNCT
flr-135	157	42	kim	kim	PROPN
flr-135	157	43	&	&	CCONJ
flr-135	157	44	ahn	ahn	PROPN
flr-135	157	45	,	,	PUNCT
flr-135	157	46	2009	2009	NUM
flr-135	157	47	)	)	PUNCT
flr-135	157	48	,	,	PUNCT
flr-135	157	49	and	and	CCONJ
flr-135	157	50	it	it	PRON
flr-135	157	51	has	have	AUX
flr-135	157	52	been	be	AUX
flr-135	157	53	found	find	VERB
flr-135	157	54	that	that	SCONJ
flr-135	157	55	neural	neural	ADJ
flr-135	157	56	networks	network	NOUN
flr-135	157	57	obtained	obtain	VERB
flr-135	157	58	better	well	ADJ
flr-135	157	59	classification	classification	NOUN
flr-135	157	60	results	result	NOUN
flr-135	157	61	.	.	PUNCT
flr-135	158	1	in	in	ADP
flr-135	158	2	fact	fact	NOUN
flr-135	158	3	,	,	PUNCT
flr-135	158	4	some	some	PRON
flr-135	158	5	of	of	ADP
flr-135	158	6	the	the	DET
flr-135	158	7	authors	author	NOUN
flr-135	158	8	in	in	ADP
flr-135	158	9	musso	musso	PROPN
flr-135	158	10	et	et	PROPN
flr-135	158	11	al	al	PROPN
flr-135	158	12	.	.	PROPN
flr-135	158	13	(	(	PUNCT
flr-135	158	14	2013	2013	NUM
flr-135	158	15	)	)	PUNCT
flr-135	158	16	already	already	ADV
flr-135	158	17	have	have	AUX
flr-135	158	18	carried	carry	VERB
flr-135	158	19	out	out	ADP
flr-135	158	20	such	such	ADJ
flr-135	158	21	analyses	analysis	NOUN
flr-135	158	22	in	in	ADP
flr-135	158	23	research	research	NOUN
flr-135	158	24	currently	currently	ADV
flr-135	158	25	underway	underway	ADJ
flr-135	158	26	,	,	PUNCT
flr-135	158	27	with	with	ADP
flr-135	158	28	the	the	DET
flr-135	158	29	same	same	ADJ
flr-135	158	30	results	result	NOUN
flr-135	158	31	favourable	favourable	ADJ
flr-135	158	32	to	to	ADP
flr-135	158	33	neural	neural	ADJ
flr-135	158	34	networks	network	NOUN
flr-135	158	35	(	(	PUNCT
flr-135	158	36	musso	musso	PROPN
flr-135	158	37	,	,	PUNCT
flr-135	158	38	boekaerts	boekaert	NOUN
flr-135	158	39	,	,	PUNCT
flr-135	158	40	segers	seger	NOUN
flr-135	158	41	,	,	PUNCT
flr-135	158	42	&	&	CCONJ
flr-135	158	43	cascallar	cascallar	ADJ
flr-135	158	44	,	,	PUNCT
flr-135	158	45	in	in	ADP
flr-135	158	46	preparation	preparation	NOUN
flr-135	158	47	)	)	PUNCT
flr-135	158	48	.	.	PUNCT
flr-135	159	1	the	the	DET
flr-135	159	2	field	field	NOUN
flr-135	159	3	of	of	ADP
flr-135	159	4	machine	machine	NOUN
flr-135	159	5	learning	learn	VERB
flr-135	159	6	research	research	NOUN
flr-135	159	7	and	and	CCONJ
flr-135	159	8	the	the	DET
flr-135	159	9	related	relate	VERB
flr-135	159	10	predictive	predictive	ADJ
flr-135	159	11	systems	system	NOUN
flr-135	159	12	is	be	AUX
flr-135	159	13	in	in	ADP
flr-135	159	14	constant	constant	ADJ
flr-135	159	15	development	development	NOUN
flr-135	159	16	and	and	CCONJ
flr-135	159	17	new	new	ADJ
flr-135	159	18	advances	advance	NOUN
flr-135	159	19	are	be	AUX
flr-135	159	20	introduced	introduce	VERB
flr-135	159	21	at	at	ADP
flr-135	159	22	a	a	DET
flr-135	159	23	rapid	rapid	ADJ
flr-135	159	24	pace	pace	NOUN
flr-135	159	25	(	(	PUNCT
flr-135	159	26	monteith	monteith	PROPN
flr-135	159	27	,	,	PUNCT
flr-135	159	28	carroll	carroll	PROPN
flr-135	159	29	,	,	PUNCT
flr-135	159	30	seppi	seppi	NOUN
flr-135	159	31	,	,	PUNCT
flr-135	159	32	&	&	CCONJ
flr-135	159	33	martinez	martinez	PROPN
flr-135	159	34	,	,	PUNCT
flr-135	159	35	2011	2011	NUM
flr-135	159	36	)	)	PUNCT
flr-135	159	37	.	.	PUNCT
flr-135	160	1	several	several	ADJ
flr-135	160	2	methods	method	NOUN
flr-135	160	3	have	have	AUX
flr-135	160	4	been	be	AUX
flr-135	160	5	suggested	suggest	VERB
flr-135	160	6	to	to	PART
flr-135	160	7	improve	improve	VERB
flr-135	160	8	the	the	DET
flr-135	160	9	performance	performance	NOUN
flr-135	160	10	of	of	ADP
flr-135	160	11	machine	machine	NOUN
flr-135	160	12	learning	learn	VERB
flr-135	160	13	algorithms	algorithm	NOUN
flr-135	160	14	and	and	CCONJ
flr-135	160	15	of	of	ADP
flr-135	160	16	neural	neural	ADJ
flr-135	160	17	network	network	NOUN
flr-135	160	18	methods	method	NOUN
flr-135	160	19	in	in	ADP
flr-135	160	20	particular	particular	ADJ
flr-135	160	21	,	,	PUNCT
flr-135	160	22	some	some	PRON
flr-135	160	23	of	of	ADP
flr-135	160	24	them	they	PRON
flr-135	160	25	using	use	VERB
flr-135	160	26	bayesian	bayesian	NOUN
flr-135	160	27	approaches	approach	NOUN
flr-135	160	28	which	which	PRON
flr-135	160	29	have	have	AUX
flr-135	160	30	shown	show	VERB
flr-135	160	31	excellent	excellent	ADJ
flr-135	160	32	potential	potential	ADJ
flr-135	160	33	(	(	PUNCT
flr-135	160	34	aires	aires	PROPN
flr-135	160	35	,	,	PUNCT
flr-135	160	36	prigent	prigent	NOUN
flr-135	160	37	,	,	PUNCT
flr-135	160	38	&	&	CCONJ
flr-135	160	39	rossow	rossow	PROPN
flr-135	160	40	,	,	PUNCT
flr-135	160	41	2004	2004	NUM
flr-135	160	42	;	;	PUNCT
flr-135	160	43	orre	orre	PROPN
flr-135	160	44	,	,	PUNCT
flr-135	160	45	lansner	lansner	NOUN
flr-135	160	46	,	,	PUNCT
flr-135	160	47	bate	bate	NOUN
flr-135	160	48	,	,	PUNCT
flr-135	160	49	&	&	CCONJ
flr-135	160	50	lindquist	lindquist	PROPN
flr-135	160	51	,	,	PUNCT
flr-135	160	52	2000	2000	NUM
flr-135	160	53	)	)	PUNCT
flr-135	160	54	.	.	PUNCT
flr-135	161	1	we	we	PRON
flr-135	161	2	share	share	VERB
flr-135	161	3	the	the	DET
flr-135	161	4	view	view	NOUN
flr-135	161	5	expressed	express	VERB
flr-135	161	6	by	by	ADP
flr-135	161	7	nokelainen	nokelainen	NOUN
flr-135	161	8	and	and	CCONJ
flr-135	161	9	silander	silander	NOUN
flr-135	161	10	(	(	PUNCT
flr-135	161	11	2014	2014	NUM
flr-135	161	12	)	)	PUNCT
flr-135	161	13	that	that	PRON
flr-135	161	14	continued	continue	VERB
flr-135	161	15	research	research	NOUN
flr-135	161	16	in	in	ADP
flr-135	161	17	this	this	DET
flr-135	161	18	field	field	NOUN
flr-135	161	19	should	should	AUX
flr-135	161	20	be	be	AUX
flr-135	161	21	pursued	pursue	VERB
flr-135	161	22	,	,	PUNCT
flr-135	161	23	and	and	CCONJ
flr-135	161	24	ensemble	ensemble	ADJ
flr-135	161	25	methods	method	NOUN
flr-135	161	26	(	(	PUNCT
flr-135	161	27	rokach	rokach	NOUN
flr-135	161	28	,	,	PUNCT
flr-135	161	29	2010	2010	NUM
flr-135	161	30	)	)	PUNCT
flr-135	161	31	,	,	PUNCT
flr-135	161	32	such	such	ADJ
flr-135	161	33	as	as	ADP
flr-135	161	34	those	those	PRON
flr-135	161	35	involving	involve	VERB
flr-135	161	36	bootstrap	bootstrap	NOUN
flr-135	161	37	aggregating	aggregating	NOUN
flr-135	161	38	(	(	PUNCT
flr-135	161	39	sahu	sahu	NOUN
flr-135	161	40	,	,	PUNCT
flr-135	161	41	runger	runger	NOUN
flr-135	161	42	,	,	PUNCT
flr-135	161	43	&	&	CCONJ
flr-135	161	44	apley	apley	PROPN
flr-135	161	45	,	,	PUNCT
flr-135	161	46	2011	2011	NUM
flr-135	161	47	)	)	PUNCT
flr-135	161	48	,	,	PUNCT
flr-135	161	49	and	and	CCONJ
flr-135	161	50	bayesian	bayesian	NOUN
flr-135	161	51	model	model	NOUN
flr-135	161	52	combination	combination	NOUN
flr-135	161	53	(	(	PUNCT
flr-135	161	54	monteith	monteith	PROPN
flr-135	161	55	et	et	PROPN
flr-135	161	56	al	al	PROPN
flr-135	161	57	.	.	PROPN
flr-135	161	58	,	,	PUNCT
flr-135	161	59	2011	2011	NUM
flr-135	161	60	)	)	PUNCT
flr-135	161	61	,	,	PUNCT
flr-135	161	62	together	together	ADV
flr-135	161	63	with	with	ADP
flr-135	161	64	multiple	multiple	ADJ
flr-135	161	65	classifier	classifier	NOUN
flr-135	161	66	systems	system	NOUN
flr-135	161	67	(	(	PUNCT
flr-135	161	68	roli	roli	NOUN
flr-135	161	69	,	,	PUNCT
flr-135	161	70	giacinto	giacinto	NOUN
flr-135	161	71	,	,	PUNCT
flr-135	161	72	&	&	CCONJ
flr-135	161	73	vernazza	vernazza	PROPN
flr-135	161	74	,	,	PUNCT
flr-135	161	75	2001	2001	NUM
flr-135	161	76	)	)	PUNCT
flr-135	161	77	are	be	AUX
flr-135	161	78	among	among	ADP
flr-135	161	79	those	those	PRON
flr-135	161	80	that	that	PRON
flr-135	161	81	should	should	AUX
flr-135	161	82	continue	continue	VERB
flr-135	161	83	to	to	PART
flr-135	161	84	be	be	AUX
flr-135	161	85	considered	consider	VERB
flr-135	161	86	in	in	ADP
flr-135	161	87	certain	certain	ADJ
flr-135	161	88	applications	application	NOUN
flr-135	161	89	.	.	PUNCT
flr-135	162	1	in	in	ADP
flr-135	162	2	conclusion	conclusion	NOUN
flr-135	162	3	,	,	PUNCT
flr-135	162	4	we	we	PRON
flr-135	162	5	can	can	AUX
flr-135	162	6	state	state	VERB
flr-135	162	7	that	that	PRON
flr-135	162	8	as	as	SCONJ
flr-135	162	9	was	be	AUX
flr-135	162	10	very	very	ADV
flr-135	162	11	accurately	accurately	ADV
flr-135	162	12	stated	state	VERB
flr-135	162	13	by	by	ADP
flr-135	162	14	anders	ander	NOUN
flr-135	162	15	and	and	CCONJ
flr-135	162	16	korn	korn	PROPN
flr-135	162	17	(	(	PUNCT
flr-135	162	18	1996	1996	NUM
flr-135	162	19	)	)	PUNCT
flr-135	162	20	in	in	ADP
flr-135	162	21	their	their	PRON
flr-135	162	22	work	work	NOUN
flr-135	162	23	on	on	ADP
flr-135	162	24	model	model	NOUN
flr-135	162	25	selection	selection	NOUN
flr-135	162	26	in	in	ADP
flr-135	162	27	neural	neural	ADJ
flr-135	162	28	networks	network	NOUN
flr-135	162	29	,	,	PUNCT
flr-135	162	30	the	the	DET
flr-135	162	31	process	process	NOUN
flr-135	162	32	of	of	ADP
flr-135	162	33	model	model	NOUN
flr-135	162	34	selection	selection	NOUN
flr-135	162	35	in	in	ADP
flr-135	162	36	ann	ann	PROPN
flr-135	162	37	can	can	AUX
flr-135	162	38	be	be	AUX
flr-135	162	39	informed	inform	VERB
flr-135	162	40	by	by	ADP
flr-135	162	41	statistical	statistical	ADJ
flr-135	162	42	procedures	procedure	NOUN
flr-135	162	43	and	and	CCONJ
flr-135	162	44	methods	method	NOUN
flr-135	162	45	.	.	PUNCT
flr-135	163	1	statistical	statistical	ADJ
flr-135	163	2	methods	method	NOUN
flr-135	163	3	can	can	AUX
flr-135	163	4	improve	improve	VERB
flr-135	163	5	the	the	DET
flr-135	163	6	model	model	NOUN
flr-135	163	7	building	building	NOUN
flr-135	163	8	and	and	CCONJ
flr-135	163	9	the	the	DET
flr-135	163	10	interpretation	interpretation	NOUN
flr-135	163	11	of	of	ADP
flr-135	163	12	anns	ann	NOUN
flr-135	163	13	.	.	PUNCT
flr-135	164	1	what	what	PRON
flr-135	164	2	is	be	AUX
flr-135	164	3	needed	need	VERB
flr-135	164	4	is	be	AUX
flr-135	164	5	the	the	DET
flr-135	164	6	courage	courage	NOUN
flr-135	164	7	and	and	CCONJ
flr-135	164	8	open	open	ADJ
flr-135	164	9	-	-	PUNCT
flr-135	164	10	mindedness	mindedness	NOUN
flr-135	164	11	to	to	PART
flr-135	164	12	actually	actually	ADV
flr-135	164	13	explore	explore	VERB
flr-135	164	14	new	new	ADJ
flr-135	164	15	paths	path	NOUN
flr-135	164	16	and	and	CCONJ
flr-135	164	17	new	new	ADJ
flr-135	164	18	methodologies	methodology	NOUN
flr-135	164	19	which	which	PRON
flr-135	164	20	can	can	AUX
flr-135	164	21	perhaps	perhaps	ADV
flr-135	164	22	sometimes	sometimes	ADV
flr-135	164	23	unexpectedly	unexpectedly	ADV
flr-135	164	24	provide	provide	VERB
flr-135	164	25	new	new	ADJ
flr-135	164	26	conceptualisations	conceptualisation	NOUN
flr-135	164	27	and	and	CCONJ
flr-135	164	28	tools	tool	NOUN
flr-135	164	29	for	for	ADP
flr-135	164	30	theoretical	theoretical	ADJ
flr-135	164	31	advancement	advancement	NOUN
flr-135	164	32	and	and	CCONJ
flr-135	164	33	practical	practical	ADJ
flr-135	164	34	applied	applied	ADJ
flr-135	164	35	research	research	NOUN
flr-135	164	36	.	.	PUNCT
flr-135	165	1	this	this	PRON
flr-135	165	2	is	be	AUX
flr-135	165	3	particularly	particularly	ADV
flr-135	165	4	true	true	ADJ
flr-135	165	5	in	in	ADP
flr-135	165	6	the	the	DET
flr-135	165	7	fields	field	NOUN
flr-135	165	8	of	of	ADP
flr-135	165	9	educational	educational	ADJ
flr-135	165	10	science	science	NOUN
flr-135	165	11	and	and	CCONJ
flr-135	165	12	social	social	ADJ
flr-135	165	13	sciences	science	NOUN
flr-135	165	14	,	,	PUNCT
flr-135	165	15	where	where	SCONJ
flr-135	165	16	the	the	DET
flr-135	165	17	complexity	complexity	NOUN
flr-135	165	18	of	of	ADP
flr-135	165	19	the	the	DET
flr-135	165	20	problems	problem	NOUN
flr-135	165	21	to	to	PART
flr-135	165	22	be	be	AUX
flr-135	165	23	solved	solve	VERB
flr-135	165	24	requires	require	VERB
flr-135	165	25	the	the	DET
flr-135	165	26	exploration	exploration	NOUN
flr-135	165	27	of	of	ADP
flr-135	165	28	proven	prove	VERB
flr-135	165	29	methods	method	NOUN
flr-135	165	30	and	and	CCONJ
flr-135	165	31	new	new	ADJ
flr-135	165	32	methods	method	NOUN
flr-135	165	33	,	,	PUNCT
flr-135	165	34	the	the	DET
flr-135	165	35	latter	latter	ADJ
flr-135	165	36	usually	usually	ADV
flr-135	165	37	not	not	PART
flr-135	165	38	among	among	ADP
flr-135	165	39	the	the	DET
flr-135	165	40	common	common	ADJ
flr-135	165	41	arsenal	arsenal	NOUN
flr-135	165	42	of	of	ADP
flr-135	165	43	tools	tool	NOUN
flr-135	165	44	of	of	ADP
flr-135	165	45	neither	neither	CCONJ
flr-135	165	46	practitioners	practitioner	NOUN
flr-135	165	47	nor	nor	CCONJ
flr-135	165	48	researchers	researcher	NOUN
flr-135	165	49	in	in	ADP
flr-135	165	50	these	these	DET
flr-135	165	51	fields	field	NOUN
flr-135	165	52	.	.	PUNCT
flr-135	166	1	keypoints	keypoint	NOUN
flr-135	166	2	artificial	artificial	ADJ
flr-135	166	3	neural	neural	ADJ
flr-135	166	4	networks	network	NOUN
flr-135	166	5	are	be	AUX
flr-135	166	6	powerful	powerful	ADJ
flr-135	166	7	mathematical	mathematical	ADJ
flr-135	166	8	modelling	modelling	NOUN
flr-135	166	9	tools	tool	NOUN
flr-135	166	10	for	for	ADP
flr-135	166	11	classification	classification	NOUN
flr-135	166	12	and	and	CCONJ
flr-135	166	13	prediction	prediction	NOUN
flr-135	166	14	.	.	PUNCT
flr-135	167	1	advances	advance	NOUN
flr-135	167	2	in	in	ADP
flr-135	167	3	artificial	artificial	ADJ
flr-135	167	4	neural	neural	ADJ
flr-135	167	5	network	network	NOUN
flr-135	167	6	methodologies	methodology	NOUN
flr-135	167	7	have	have	AUX
flr-135	167	8	made	make	VERB
flr-135	167	9	them	they	PRON
flr-135	167	10	more	more	ADV
flr-135	167	11	transparent	transparent	ADJ
flr-135	167	12	and	and	CCONJ
flr-135	167	13	useful	useful	ADJ
flr-135	167	14	,	,	PUNCT
flr-135	167	15	avoiding	avoid	VERB
flr-135	167	16	the	the	DET
flr-135	167	17	original	original	ADJ
flr-135	167	18	“	"	PUNCT
flr-135	167	19	black	black	ADJ
flr-135	167	20	box	box	NOUN
flr-135	167	21	”	"	PUNCT
flr-135	167	22	characteristics	characteristic	NOUN
flr-135	167	23	in	in	ADP
flr-135	167	24	their	their	PRON
flr-135	167	25	early	early	ADJ
flr-135	167	26	development	development	NOUN
flr-135	167	27	.	.	PUNCT
flr-135	168	1	there	there	PRON
flr-135	168	2	is	be	VERB
flr-135	168	3	a	a	DET
flr-135	168	4	long	long	ADJ
flr-135	168	5	history	history	NOUN
flr-135	168	6	with	with	ADP
flr-135	168	7	significant	significant	ADJ
flr-135	168	8	recent	recent	ADJ
flr-135	168	9	advances	advance	NOUN
flr-135	168	10	which	which	PRON
flr-135	168	11	has	have	AUX
flr-135	168	12	achieved	achieve	VERB
flr-135	168	13	strong	strong	ADJ
flr-135	168	14	ties	tie	NOUN
flr-135	168	15	between	between	ADP
flr-135	168	16	traditional	traditional	ADJ
flr-135	168	17	statistical	statistical	ADJ
flr-135	168	18	constructs	construct	NOUN
flr-135	168	19	with	with	ADP
flr-135	168	20	their	their	PRON
flr-135	168	21	equivalent	equivalent	NOUN
flr-135	168	22	in	in	ADP
flr-135	168	23	artificial	artificial	ADJ
flr-135	168	24	neural	neural	ADJ
flr-135	168	25	networks	network	NOUN
flr-135	168	26	.	.	PUNCT
flr-135	169	1	artificial	artificial	ADJ
flr-135	169	2	neural	neural	ADJ
flr-135	169	3	networks	network	NOUN
flr-135	169	4	are	be	AUX
flr-135	169	5	a	a	DET
flr-135	169	6	useful	useful	ADJ
flr-135	169	7	methodology	methodology	NOUN
flr-135	169	8	that	that	PRON
flr-135	169	9	can	can	AUX
flr-135	169	10	advance	advance	VERB
flr-135	169	11	our	our	PRON
flr-135	169	12	understanding	understanding	NOUN
flr-135	169	13	of	of	ADP
flr-135	169	14	phenomena	phenomenon	NOUN
flr-135	169	15	when	when	SCONJ
flr-135	169	16	modelling	model	VERB
flr-135	169	17	for	for	ADP
flr-135	169	18	understanding	understanding	NOUN
flr-135	169	19	and	and	CCONJ
flr-135	169	20	modelling	modelling	NOUN
flr-135	169	21	for	for	ADP
flr-135	169	22	classification	classification	NOUN
flr-135	169	23	/	/	SYM
flr-135	169	24	predictions	prediction	NOUN
flr-135	169	25	are	be	AUX
flr-135	169	26	combined	combine	VERB
flr-135	169	27	.	.	PUNCT
flr-135	170	1	cascallar	cascallar	INTJ
flr-135	170	2	et	et	PROPN
flr-135	170	3	al	al	PROPN
flr-135	170	4	76	76	NUM
flr-135	171	1	|	|	INTJ
flr-135	171	2	f	f	NOUN
flr-135	171	3	l	l	NOUN
flr-135	171	4	r	r	NOUN
flr-135	171	5	artificial	artificial	ADJ
flr-135	171	6	neural	neural	ADJ
flr-135	171	7	networks	network	NOUN
flr-135	171	8	are	be	AUX
flr-135	171	9	an	an	DET
flr-135	171	10	additional	additional	ADJ
flr-135	171	11	important	important	ADJ
flr-135	171	12	tool	tool	NOUN
flr-135	171	13	in	in	ADP
flr-135	171	14	the	the	DET
flr-135	171	15	researcher‟s	researcher‟s	PROPN
flr-135	171	16	toolbox	toolbox	NOUN
flr-135	171	17	which	which	PRON
flr-135	171	18	can	can	AUX
flr-135	171	19	be	be	AUX
flr-135	171	20	particularly	particularly	ADV
flr-135	171	21	useful	useful	ADJ
flr-135	171	22	to	to	PART
flr-135	171	23	tackle	tackle	VERB
flr-135	171	24	highly	highly	ADV
flr-135	171	25	complex	complex	ADJ
flr-135	171	26	and	and	CCONJ
flr-135	171	27	large	large	ADJ
flr-135	171	28	data	datum	NOUN
flr-135	171	29	sets	set	NOUN
flr-135	171	30	with	with	ADP
flr-135	171	31	interactions	interaction	NOUN
flr-135	171	32	among	among	ADP
flr-135	171	33	the	the	DET
flr-135	171	34	variables	variable	NOUN
flr-135	171	35	which	which	PRON
flr-135	171	36	are	be	AUX
flr-135	171	37	not	not	PART
flr-135	171	38	fully	fully	ADV
flr-135	171	39	understood	understand	VERB
flr-135	171	40	.	.	PUNCT
flr-135	172	1	references	reference	NOUN
flr-135	172	2	agrawal	agrawal	PROPN
flr-135	172	3	,	,	PUNCT
flr-135	172	4	a.	a.	NOUN
flr-135	172	5	(	(	PUNCT
flr-135	172	6	2001	2001	NUM
flr-135	172	7	)	)	PUNCT
flr-135	172	8	.	.	PUNCT
flr-135	173	1	common	common	ADJ
flr-135	173	2	property	property	NOUN
flr-135	173	3	institutions	institution	NOUN
flr-135	173	4	and	and	CCONJ
flr-135	173	5	sustainable	sustainable	ADJ
flr-135	173	6	governance	governance	NOUN
flr-135	173	7	of	of	ADP
flr-135	173	8	resources	resource	NOUN
flr-135	173	9	.	.	PUNCT
flr-135	174	1	world	world	NOUN
flr-135	174	2	development	development	PROPN
flr-135	174	3	,	,	PUNCT
flr-135	174	4	29	29	NUM
flr-135	174	5	,	,	PUNCT
flr-135	174	6	1649	1649	NUM
flr-135	174	7	-	-	SYM
flr-135	174	8	1672	1672	NUM
flr-135	174	9	.	.	PUNCT
flr-135	175	1	doi	doi	NOUN
flr-135	175	2	:	:	PUNCT
flr-135	175	3	10.1016	10.1016	NUM
flr-135	175	4	/	/	SYM
flr-135	175	5	s0305	s0305	PROPN
flr-135	175	6	-	-	PUNCT
flr-135	175	7	750x(01)00063	750x(01)00063	NUM
flr-135	175	8	-	-	PUNCT
flr-135	175	9	8	8	NUM
flr-135	175	10	agrawal	agrawal	PROPN
flr-135	175	11	,	,	PUNCT
flr-135	175	12	a.	a.	NOUN
flr-135	175	13	,	,	PUNCT
flr-135	175	14	&	&	CCONJ
flr-135	175	15	chhatre	chhatre	PROPN
flr-135	175	16	,	,	PUNCT
flr-135	175	17	a.	a.	NOUN
flr-135	175	18	(	(	PUNCT
flr-135	175	19	2006	2006	NUM
flr-135	175	20	)	)	PUNCT
flr-135	175	21	.	.	PUNCT
flr-135	176	1	explaining	explain	VERB
flr-135	176	2	success	success	NOUN
flr-135	176	3	on	on	ADP
flr-135	176	4	the	the	DET
flr-135	176	5	commons	common	NOUN
flr-135	176	6	:	:	PUNCT
flr-135	176	7	community	community	NOUN
flr-135	176	8	forest	forest	NOUN
flr-135	176	9	governance	governance	NOUN
flr-135	176	10	in	in	ADP
flr-135	176	11	the	the	DET
flr-135	176	12	indian	indian	PROPN
flr-135	176	13	himalaya	himalaya	PROPN
flr-135	176	14	.	.	PUNCT
flr-135	177	1	world	world	PROPN
flr-135	177	2	development	development	PROPN
flr-135	177	3	,	,	PUNCT
flr-135	177	4	34	34	NUM
flr-135	177	5	,	,	PUNCT
flr-135	177	6	149	149	NUM
flr-135	177	7	-	-	SYM
flr-135	177	8	166	166	NUM
flr-135	177	9	.	.	PUNCT
flr-135	178	1	doi	doi	NOUN
flr-135	178	2	:	:	PUNCT
flr-135	178	3	10.1016	10.1016	NUM
flr-135	178	4	/	/	SYM
flr-135	178	5	j.worlddev.2005.07.013	j.worlddev.2005.07.013	PROPN
flr-135	178	6	aires	aires	PROPN
flr-135	178	7	,	,	PUNCT
flr-135	178	8	f.	f.	PROPN
flr-135	178	9	,	,	PUNCT
flr-135	178	10	prigent	prigent	PROPN
flr-135	178	11	,	,	PUNCT
flr-135	178	12	c.	c.	PROPN
flr-135	178	13	,	,	PUNCT
flr-135	178	14	&	&	CCONJ
flr-135	178	15	rossow	rossow	PROPN
flr-135	178	16	,	,	PUNCT
flr-135	178	17	w.	w.	PROPN
flr-135	178	18	b.	b.	PROPN
flr-135	178	19	(	(	PUNCT
flr-135	178	20	2004	2004	NUM
flr-135	178	21	)	)	PUNCT
flr-135	178	22	.	.	PUNCT
flr-135	179	1	neural	neural	ADJ
flr-135	179	2	network	network	NOUN
flr-135	179	3	uncertainty	uncertainty	NOUN
flr-135	179	4	assessment	assessment	NOUN
flr-135	179	5	using	use	VERB
flr-135	179	6	bayesian	bayesian	NOUN
flr-135	179	7	statistics	statistic	NOUN
flr-135	179	8	:	:	PUNCT
flr-135	179	9	a	a	DET
flr-135	179	10	remote	remote	ADJ
flr-135	179	11	sensing	sense	VERB
flr-135	179	12	application	application	NOUN
flr-135	179	13	.	.	PUNCT
flr-135	180	1	neural	neural	ADJ
flr-135	180	2	computing	computing	NOUN
flr-135	180	3	,	,	PUNCT
flr-135	180	4	16	16	NUM
flr-135	180	5	,	,	PUNCT
flr-135	180	6	2415	2415	NUM
flr-135	180	7	-	-	SYM
flr-135	180	8	2458	2458	NUM
flr-135	180	9	.	.	PUNCT
flr-135	181	1	doi	doi	NOUN
flr-135	181	2	:	:	PUNCT
flr-135	181	3	10.1162/0899766041941925	10.1162/0899766041941925	NUM
flr-135	181	4	al	al	PROPN
flr-135	181	5	-	-	PUNCT
flr-135	181	6	deek	deek	PROPN
flr-135	181	7	,	,	PUNCT
flr-135	181	8	h.	h.	PROPN
flr-135	181	9	m.	m.	NOUN
flr-135	181	10	(	(	PUNCT
flr-135	181	11	2001	2001	NUM
flr-135	181	12	)	)	PUNCT
flr-135	181	13	.	.	PUNCT
flr-135	182	1	which	which	DET
flr-135	182	2	method	method	NOUN
flr-135	182	3	is	be	AUX
flr-135	182	4	better	well	ADJ
flr-135	182	5	for	for	ADP
flr-135	182	6	developing	develop	VERB
flr-135	182	7	freight	freight	NOUN
flr-135	182	8	planning	planning	NOUN
flr-135	182	9	models	model	NOUN
flr-135	182	10	at	at	ADP
flr-135	182	11	seaports	seaport	NOUN
flr-135	182	12	–	–	PUNCT
flr-135	182	13	neural	neural	ADJ
flr-135	182	14	networks	network	NOUN
flr-135	182	15	or	or	CCONJ
flr-135	182	16	multiple	multiple	ADJ
flr-135	182	17	regression	regression	NOUN
flr-135	182	18	?	?	PUNCT
flr-135	183	1	transportation	transportation	NOUN
flr-135	183	2	research	research	NOUN
flr-135	183	3	record	record	NOUN
flr-135	183	4	,	,	PUNCT
flr-135	183	5	1763	1763	NUM
flr-135	183	6	,	,	PUNCT
flr-135	183	7	9097	9097	NUM
flr-135	183	8	.	.	PUNCT
flr-135	184	1	doi	doi	NOUN
flr-135	184	2	:	:	PUNCT
flr-135	184	3	10.3141/176314	10.3141/176314	NUM
flr-135	184	4	anders	ander	NOUN
flr-135	184	5	,	,	PUNCT
flr-135	184	6	u.	u.	PROPN
flr-135	184	7	,	,	PUNCT
flr-135	184	8	&	&	CCONJ
flr-135	184	9	korn	korn	PROPN
flr-135	184	10	,	,	PUNCT
flr-135	184	11	o.	o.	PROPN
flr-135	184	12	(	(	PUNCT
flr-135	184	13	1996	1996	NUM
flr-135	184	14	)	)	PUNCT
flr-135	184	15	.	.	PUNCT
flr-135	185	1	model	model	NOUN
flr-135	185	2	selection	selection	NOUN
flr-135	185	3	in	in	ADP
flr-135	185	4	neural	neural	ADJ
flr-135	185	5	networks	network	NOUN
flr-135	185	6	.	.	PUNCT
flr-135	186	1	zew	zew	NOUN
flr-135	186	2	discussion	discussion	NOUN
flr-135	186	3	papers	paper	NOUN
flr-135	186	4	,	,	PUNCT
flr-135	186	5	96	96	NUM
flr-135	186	6	-	-	SYM
flr-135	186	7	21	21	NUM
flr-135	186	8	.	.	PUNCT
flr-135	186	9	retrieved	retrieve	VERB
flr-135	186	10	from	from	ADP
flr-135	186	11	http://hdl.handle.net/10419/29449	http://hdl.handle.net/10419/29449	PROPN
flr-135	186	12	ansari	ansari	PROPN
flr-135	186	13	,	,	PUNCT
flr-135	186	14	a.	a.	NOUN
flr-135	186	15	,	,	PUNCT
flr-135	186	16	jedidi	jedidi	PROPN
flr-135	186	17	,	,	PUNCT
flr-135	186	18	k.	k.	PROPN
flr-135	186	19	,	,	PUNCT
flr-135	186	20	&	&	CCONJ
flr-135	186	21	jagpal	jagpal	PROPN
flr-135	186	22	,	,	PUNCT
flr-135	186	23	h.	h.	PROPN
flr-135	186	24	s.	s.	PROPN
flr-135	186	25	(	(	PUNCT
flr-135	186	26	2000	2000	NUM
flr-135	186	27	)	)	PUNCT
flr-135	186	28	.	.	PUNCT
flr-135	187	1	a	a	DET
flr-135	187	2	hierarchical	hierarchical	ADJ
flr-135	187	3	bayesian	bayesian	NOUN
flr-135	187	4	methodology	methodology	NOUN
flr-135	187	5	for	for	ADP
flr-135	187	6	treating	treat	VERB
flr-135	187	7	heterogeneity	heterogeneity	NOUN
flr-135	187	8	in	in	ADP
flr-135	187	9	structural	structural	ADJ
flr-135	187	10	equation	equation	NOUN
flr-135	187	11	models	model	NOUN
flr-135	187	12	.	.	PUNCT
flr-135	188	1	marketing	marketing	NOUN
flr-135	188	2	science	science	NOUN
flr-135	188	3	,	,	PUNCT
flr-135	188	4	19	19	NUM
flr-135	188	5	,	,	PUNCT
flr-135	188	6	328	328	NUM
flr-135	188	7	-	-	SYM
flr-135	188	8	347	347	NUM
flr-135	188	9	.	.	PUNCT
flr-135	189	1	doi	doi	NOUN
flr-135	189	2	:	:	PUNCT
flr-135	189	3	10.1287	10.1287	NUM
flr-135	189	4	/	/	SYM
flr-135	189	5	mksc.19.4.328.11789	mksc.19.4.328.11789	SYM
flr-135	189	6	benitez	benitez	PROPN
flr-135	189	7	,	,	PUNCT
flr-135	189	8	j.	j.	PROPN
flr-135	189	9	m.	m.	PROPN
flr-135	189	10	,	,	PUNCT
flr-135	189	11	castro	castro	PROPN
flr-135	189	12	,	,	PUNCT
flr-135	189	13	j.	j.	PROPN
flr-135	189	14	l.	l.	PROPN
flr-135	189	15	,	,	PUNCT
flr-135	189	16	&	&	CCONJ
flr-135	189	17	requena	requena	PROPN
flr-135	189	18	,	,	PUNCT
flr-135	189	19	i.	i.	NOUN
flr-135	189	20	(	(	PUNCT
flr-135	189	21	1997	1997	NUM
flr-135	189	22	)	)	PUNCT
flr-135	189	23	.	.	PUNCT
flr-135	190	1	are	be	AUX
flr-135	190	2	artificial	artificial	ADJ
flr-135	190	3	neural	neural	ADJ
flr-135	190	4	networks	network	NOUN
flr-135	190	5	black	black	ADJ
flr-135	190	6	boxes	box	NOUN
flr-135	190	7	?	?	PUNCT
flr-135	191	1	ieee	ieee	NOUN
flr-135	191	2	transactions	transaction	NOUN
flr-135	191	3	on	on	ADP
flr-135	191	4	neural	neural	ADJ
flr-135	191	5	networks	network	NOUN
flr-135	191	6	,	,	PUNCT
flr-135	191	7	8	8	NUM
flr-135	191	8	,	,	PUNCT
flr-135	191	9	1156	1156	NUM
flr-135	191	10	-	-	SYM
flr-135	191	11	1164	1164	NUM
flr-135	191	12	.	.	PUNCT
flr-135	192	1	doi	doi	NOUN
flr-135	192	2	:	:	PUNCT
flr-135	192	3	10.1109/72.623216	10.1109/72.623216	NUM
flr-135	192	4	blackard	blackard	NOUN
flr-135	192	5	,	,	PUNCT
flr-135	192	6	j.	j.	PROPN
flr-135	192	7	a.	a.	PROPN
flr-135	192	8	&	&	CCONJ
flr-135	192	9	dean	dean	PROPN
flr-135	192	10	,	,	PUNCT
flr-135	192	11	d.	d.	PROPN
flr-135	192	12	j.	j.	PROPN
flr-135	192	13	(	(	PUNCT
flr-135	192	14	1999	1999	NUM
flr-135	192	15	)	)	PUNCT
flr-135	192	16	.	.	PUNCT
flr-135	193	1	comparative	comparative	ADJ
flr-135	193	2	accuracies	accuracy	NOUN
flr-135	193	3	of	of	ADP
flr-135	193	4	artificial	artificial	ADJ
flr-135	193	5	neural	neural	ADJ
flr-135	193	6	networks	network	NOUN
flr-135	193	7	and	and	CCONJ
flr-135	193	8	discriminant	discriminant	ADJ
flr-135	193	9	analysis	analysis	NOUN
flr-135	193	10	in	in	ADP
flr-135	193	11	predicting	predict	VERB
flr-135	193	12	forest	forest	NOUN
flr-135	193	13	cover	cover	NOUN
flr-135	193	14	types	type	NOUN
flr-135	193	15	from	from	ADP
flr-135	193	16	cartographic	cartographic	ADJ
flr-135	193	17	variables	variable	NOUN
flr-135	193	18	.	.	PUNCT
flr-135	194	1	computers	computer	NOUN
flr-135	194	2	and	and	CCONJ
flr-135	194	3	electronics	electronic	NOUN
flr-135	194	4	in	in	ADP
flr-135	194	5	agriculture	agriculture	NOUN
flr-135	194	6	,	,	PUNCT
flr-135	194	7	24	24	NUM
flr-135	194	8	,	,	PUNCT
flr-135	194	9	131–151	131–151	NUM
flr-135	194	10	.	.	PUNCT
flr-135	195	1	doi	doi	NOUN
flr-135	195	2	:	:	PUNCT
flr-135	195	3	10.1016	10.1016	NUM
flr-135	195	4	/	/	SYM
flr-135	195	5	s0168	s0168	PROPN
flr-135	195	6	-	-	PUNCT
flr-135	195	7	1699(99)00046	1699(99)00046	NUM
flr-135	195	8	-	-	SYM
flr-135	195	9	0	0	NUM
flr-135	195	10	boekaerts	boekaert	NOUN
flr-135	195	11	,	,	PUNCT
flr-135	195	12	m.	m.	NOUN
flr-135	195	13	,	,	PUNCT
flr-135	195	14	&	&	CCONJ
flr-135	195	15	cascallar	cascallar	PROPN
flr-135	195	16	,	,	PUNCT
flr-135	195	17	e.	e.	PROPN
flr-135	195	18	c.	c.	PROPN
flr-135	195	19	(	(	PUNCT
flr-135	195	20	2006	2006	NUM
flr-135	195	21	)	)	PUNCT
flr-135	195	22	.	.	PUNCT
flr-135	196	1	how	how	SCONJ
flr-135	196	2	far	far	ADV
flr-135	196	3	have	have	AUX
flr-135	196	4	we	we	PRON
flr-135	196	5	moved	move	VERB
flr-135	196	6	toward	toward	ADP
flr-135	196	7	the	the	DET
flr-135	196	8	integration	integration	NOUN
flr-135	196	9	of	of	ADP
flr-135	196	10	theory	theory	NOUN
flr-135	196	11	and	and	CCONJ
flr-135	196	12	practice	practice	NOUN
flr-135	196	13	in	in	ADP
flr-135	196	14	self	self	NOUN
flr-135	196	15	-	-	PUNCT
flr-135	196	16	regulation	regulation	NOUN
flr-135	196	17	?	?	PUNCT
flr-135	197	1	educational	educational	ADJ
flr-135	197	2	psychology	psychology	NOUN
flr-135	197	3	review	review	NOUN
flr-135	197	4	,	,	PUNCT
flr-135	197	5	18	18	NUM
flr-135	197	6	,	,	PUNCT
flr-135	197	7	199	199	NUM
flr-135	197	8	-	-	SYM
flr-135	197	9	210	210	NUM
flr-135	197	10	.	.	PUNCT
flr-135	198	1	doi	doi	NOUN
flr-135	198	2	:	:	PUNCT
flr-135	198	3	10.1007	10.1007	NUM
flr-135	198	4	/	/	SYM
flr-135	198	5	s10648	s10648	NOUN
flr-135	198	6	-	-	PUNCT
flr-135	198	7	0069013	0069013	NUM
flr-135	198	8	-	-	PUNCT
flr-135	198	9	4	4	NUM
flr-135	198	10	bridle	bridle	NOUN
flr-135	198	11	,	,	PUNCT
flr-135	198	12	j.	j.	PROPN
flr-135	198	13	s.	s.	PROPN
flr-135	198	14	(	(	PUNCT
flr-135	198	15	1992	1992	NUM
flr-135	198	16	)	)	PUNCT
flr-135	198	17	.	.	PUNCT
flr-135	199	1	neural	neural	ADJ
flr-135	199	2	networks	network	NOUN
flr-135	199	3	or	or	CCONJ
flr-135	199	4	hidden	hide	VERB
flr-135	199	5	markov	markov	NOUN
flr-135	199	6	models	model	NOUN
flr-135	199	7	for	for	ADP
flr-135	199	8	automatic	automatic	ADJ
flr-135	199	9	speech	speech	NOUN
flr-135	199	10	recognition	recognition	NOUN
flr-135	199	11	:	:	PUNCT
flr-135	199	12	is	be	AUX
flr-135	199	13	there	there	PRON
flr-135	199	14	a	a	DET
flr-135	199	15	choice	choice	NOUN
flr-135	199	16	?	?	PUNCT
flr-135	200	1	in	in	ADP
flr-135	200	2	p.	p.	NOUN
flr-135	200	3	laface	laface	NOUN
flr-135	200	4	(	(	PUNCT
flr-135	200	5	ed	ed	NOUN
flr-135	200	6	.	.	PUNCT
flr-135	200	7	)	)	PUNCT
flr-135	200	8	,	,	PUNCT
flr-135	200	9	speech	speech	NOUN
flr-135	200	10	recognition	recognition	NOUN
flr-135	200	11	and	and	CCONJ
flr-135	200	12	understanding	understanding	NOUN
flr-135	200	13	:	:	PUNCT
flr-135	200	14	recent	recent	ADJ
flr-135	200	15	advances	advance	NOUN
flr-135	200	16	,	,	PUNCT
flr-135	200	17	trends	trend	NOUN
flr-135	200	18	and	and	CCONJ
flr-135	200	19	application	application	NOUN
flr-135	200	20	(	(	PUNCT
flr-135	200	21	pp	pp	ADJ
flr-135	200	22	.	.	PUNCT
flr-135	200	23	225	225	NUM
flr-135	200	24	-	-	SYM
flr-135	200	25	236	236	NUM
flr-135	200	26	)	)	PUNCT
flr-135	200	27	.	.	PUNCT
flr-135	201	1	new	new	PROPN
flr-135	201	2	york	york	PROPN
flr-135	201	3	:	:	PUNCT
flr-135	201	4	springer	springer	NOUN
flr-135	201	5	.	.	PUNCT
flr-135	202	1	cascallar	cascallar	PROPN
flr-135	202	2	,	,	PUNCT
flr-135	202	3	e.	e.	PROPN
flr-135	202	4	c.	c.	PROPN
flr-135	202	5	,	,	PUNCT
flr-135	202	6	boekaerts	boekaert	NOUN
flr-135	202	7	,	,	PUNCT
flr-135	202	8	m.	m.	NOUN
flr-135	202	9	,	,	PUNCT
flr-135	202	10	&	&	CCONJ
flr-135	202	11	costigan	costigan	NOUN
flr-135	202	12	,	,	PUNCT
flr-135	202	13	t.	t.	PROPN
flr-135	202	14	e.	e.	PROPN
flr-135	202	15	(	(	PUNCT
flr-135	202	16	2006	2006	NUM
flr-135	202	17	)	)	PUNCT
flr-135	202	18	assessment	assessment	NOUN
flr-135	202	19	in	in	ADP
flr-135	202	20	the	the	DET
flr-135	202	21	evaluation	evaluation	NOUN
flr-135	202	22	of	of	ADP
flr-135	202	23	selfregulation	selfregulation	NOUN
flr-135	202	24	as	as	ADP
flr-135	202	25	a	a	DET
flr-135	202	26	process	process	NOUN
flr-135	202	27	.	.	PUNCT
flr-135	203	1	educational	educational	ADJ
flr-135	203	2	psychology	psychology	NOUN
flr-135	203	3	review	review	PROPN
flr-135	203	4	,	,	PUNCT
flr-135	203	5	18	18	NUM
flr-135	203	6	,	,	PUNCT
flr-135	203	7	297	297	NUM
flr-135	203	8	-	-	SYM
flr-135	203	9	306	306	NUM
flr-135	203	10	.	.	PUNCT
flr-135	204	1	doi	doi	NOUN
flr-135	204	2	:	:	PUNCT
flr-135	204	3	10.1007	10.1007	NUM
flr-135	204	4	/	/	SYM
flr-135	204	5	s10648	s10648	NOUN
flr-135	204	6	-	-	PUNCT
flr-135	204	7	006	006	NUM
flr-135	204	8	-	-	PUNCT
flr-135	204	9	9023	9023	NUM
flr-135	204	10	-	-	SYM
flr-135	204	11	2	2	NUM
flr-135	204	12	http://dx.doi.org/10.1016/s0305-750x(01)00063-8	http://dx.doi.org/10.1016/s0305-750x(01)00063-8	VERB
flr-135	204	13	http://dx.doi.org/10.1016/j.worlddev.2005.07.013	http://dx.doi.org/10.1016/j.worlddev.2005.07.013	PROPN
flr-135	204	14	http://dx.doi.org/10.1162/0899766041941925	http://dx.doi.org/10.1162/0899766041941925	PROPN
flr-135	204	15	http://dx.doi.org/10.3141/1763-14	http://dx.doi.org/10.3141/1763-14	PROPN
flr-135	204	16	http://dx.doi.org/10.3141/1763-14	http://dx.doi.org/10.3141/1763-14	PROPN
flr-135	204	17	http://hdl.handle.net/10419/29449	http://hdl.handle.net/10419/29449	PROPN
flr-135	204	18	http://dx.doi.org/10.1287/mksc.19.4.328.11789	http://dx.doi.org/10.1287/mksc.19.4.328.11789	PROPN
flr-135	204	19	http://dx.doi.org/10.1109/72.623216	http://dx.doi.org/10.1109/72.623216	PROPN
flr-135	204	20	http://dx.doi.org/10.1016/s0168-1699(99)00046-0	http://dx.doi.org/10.1016/s0168-1699(99)00046-0	PROPN
flr-135	204	21	http://dx.doi.org/10.1007/s10648-006-9013-4	http://dx.doi.org/10.1007/s10648-006-9013-4	PROPN
flr-135	204	22	http://dx.doi.org/10.1007/s10648-006-9013-4	http://dx.doi.org/10.1007/s10648-006-9013-4	PROPN
flr-135	204	23	http://dx.doi.org/10.1007/s10648-006-9023-2	http://dx.doi.org/10.1007/s10648-006-9023-2	PROPN
flr-135	205	1	cascallar	cascallar	PROPN
flr-135	205	2	et	et	PROPN
flr-135	206	1	al	al	PROPN
flr-135	206	2	77	77	NUM
flr-135	207	1	|	|	CCONJ
flr-135	207	2	f	f	NOUN
flr-135	207	3	l	l	NOUN
flr-135	207	4	r	r	PROPN
flr-135	207	5	cheng	cheng	PROPN
flr-135	207	6	,	,	PUNCT
flr-135	207	7	b.	b.	PROPN
flr-135	207	8	,	,	PUNCT
flr-135	207	9	&	&	CCONJ
flr-135	207	10	titterington	titterington	PROPN
flr-135	207	11	,	,	PUNCT
flr-135	207	12	d.	d.	PROPN
flr-135	207	13	m.	m.	PROPN
flr-135	207	14	(	(	PUNCT
flr-135	207	15	1994	1994	NUM
flr-135	207	16	)	)	PUNCT
flr-135	207	17	.	.	PUNCT
flr-135	208	1	neural	neural	ADJ
flr-135	208	2	networks	network	NOUN
flr-135	208	3	:	:	PUNCT
flr-135	208	4	a	a	DET
flr-135	208	5	review	review	NOUN
flr-135	208	6	from	from	ADP
flr-135	208	7	a	a	DET
flr-135	208	8	statistical	statistical	ADJ
flr-135	208	9	perspective	perspective	NOUN
flr-135	208	10	.	.	PUNCT
flr-135	209	1	statistical	statistical	ADJ
flr-135	209	2	science	science	NOUN
flr-135	209	3	,	,	PUNCT
flr-135	209	4	9	9	NUM
flr-135	209	5	,	,	PUNCT
flr-135	209	6	1	1	NUM
flr-135	209	7	,	,	PUNCT
flr-135	209	8	2	2	NUM
flr-135	209	9	-	-	SYM
flr-135	209	10	54	54	NUM
flr-135	209	11	.	.	PUNCT
flr-135	210	1	doi	doi	NOUN
flr-135	210	2	:	:	PUNCT
flr-135	210	3	10.1214	10.1214	NUM
flr-135	210	4	/	/	SYM
flr-135	210	5	ss/1177010638	ss/1177010638	NOUN
flr-135	210	6	chin	chin	NOUN
flr-135	210	7	,	,	PUNCT
flr-135	210	8	w.	w.	PROPN
flr-135	210	9	w.	w.	PROPN
flr-135	210	10	,	,	PUNCT
flr-135	210	11	marcolin	marcolin	PROPN
flr-135	210	12	,	,	PUNCT
flr-135	210	13	b.	b.	PROPN
flr-135	210	14	l.	l.	PROPN
flr-135	210	15	,	,	PUNCT
flr-135	210	16	&	&	CCONJ
flr-135	210	17	newsted	newste	VERB
flr-135	210	18	,	,	PUNCT
flr-135	210	19	p.	p.	PROPN
flr-135	210	20	r.	r.	PROPN
flr-135	210	21	(	(	PUNCT
flr-135	210	22	2003	2003	NUM
flr-135	210	23	)	)	PUNCT
flr-135	210	24	.	.	PUNCT
flr-135	211	1	a	a	DET
flr-135	211	2	partial	partial	ADJ
flr-135	211	3	least	least	ADJ
flr-135	211	4	squares	square	NOUN
flr-135	211	5	latent	latent	ADJ
flr-135	211	6	variable	variable	NOUN
flr-135	211	7	modelling	model	VERB
flr-135	211	8	approach	approach	NOUN
flr-135	211	9	for	for	ADP
flr-135	211	10	measuring	measure	VERB
flr-135	211	11	interaction	interaction	NOUN
flr-135	211	12	effects	effect	NOUN
flr-135	211	13	:	:	PUNCT
flr-135	211	14	results	result	NOUN
flr-135	211	15	from	from	ADP
flr-135	211	16	a	a	DET
flr-135	211	17	monte	monte	PROPN
flr-135	211	18	carlo	carlo	PROPN
flr-135	211	19	simulation	simulation	PROPN
flr-135	211	20	study	study	PROPN
flr-135	211	21	and	and	CCONJ
flr-135	211	22	an	an	DET
flr-135	211	23	electronic	electronic	ADJ
flr-135	211	24	-	-	PUNCT
flr-135	211	25	mail	mail	NOUN
flr-135	211	26	emotion	emotion	NOUN
flr-135	211	27	/	/	SYM
flr-135	211	28	adoption	adoption	NOUN
flr-135	211	29	study	study	NOUN
flr-135	211	30	.	.	PUNCT
flr-135	212	1	information	information	NOUN
flr-135	212	2	systems	system	NOUN
flr-135	212	3	research	research	NOUN
flr-135	212	4	,	,	PUNCT
flr-135	212	5	14	14	NUM
flr-135	212	6	,	,	PUNCT
flr-135	212	7	189–217	189–217	NUM
flr-135	212	8	.	.	PUNCT
flr-135	213	1	doi	doi	NOUN
flr-135	213	2	:	:	PUNCT
flr-135	213	3	10.1287	10.1287	NUM
flr-135	213	4	/	/	SYM
flr-135	213	5	isre.14.2.189.16018	isre.14.2.189.16018	PROPN
flr-135	213	6	decuyper	decuyper	NOUN
flr-135	213	7	,	,	PUNCT
flr-135	213	8	s.	s.	PROPN
flr-135	213	9	,	,	PUNCT
flr-135	213	10	dochy	dochy	NOUN
flr-135	213	11	,	,	PUNCT
flr-135	213	12	f.	f.	PROPN
flr-135	213	13	,	,	PUNCT
flr-135	213	14	&	&	CCONJ
flr-135	213	15	van	van	PROPN
flr-135	213	16	den	den	PROPN
flr-135	213	17	bossche	bossche	PROPN
flr-135	213	18	,	,	PUNCT
flr-135	213	19	p.	p.	NOUN
flr-135	213	20	(	(	PUNCT
flr-135	213	21	2010	2010	NUM
flr-135	213	22	)	)	PUNCT
flr-135	213	23	.	.	PUNCT
flr-135	214	1	grasping	grasp	VERB
flr-135	214	2	the	the	DET
flr-135	214	3	dynamic	dynamic	ADJ
flr-135	214	4	complexity	complexity	NOUN
flr-135	214	5	of	of	ADP
flr-135	214	6	team	team	NOUN
flr-135	214	7	learning	learn	VERB
flr-135	214	8	:	:	PUNCT
flr-135	214	9	an	an	DET
flr-135	214	10	integrative	integrative	ADJ
flr-135	214	11	model	model	NOUN
flr-135	214	12	for	for	ADP
flr-135	214	13	effective	effective	ADJ
flr-135	214	14	team	team	NOUN
flr-135	214	15	learning	learn	VERB
flr-135	214	16	in	in	ADP
flr-135	214	17	organisations	organisation	NOUN
flr-135	214	18	.	.	PUNCT
flr-135	215	1	educational	educational	ADJ
flr-135	215	2	research	research	PROPN
flr-135	215	3	review	review	PROPN
flr-135	215	4	,	,	PUNCT
flr-135	215	5	5	5	NUM
flr-135	215	6	,	,	PUNCT
flr-135	215	7	111	111	NUM
flr-135	215	8	-	-	SYM
flr-135	215	9	133	133	NUM
flr-135	215	10	.	.	PUNCT
flr-135	216	1	doi	doi	NOUN
flr-135	216	2	:	:	PUNCT
flr-135	216	3	10.1016	10.1016	NUM
flr-135	216	4	/	/	SYM
flr-135	216	5	j.edurev.2010.02.002	j.edurev.2010.02.002	PROPN
flr-135	216	6	detienne	detienne	PROPN
flr-135	216	7	,	,	PUNCT
flr-135	216	8	k.	k.	PROPN
flr-135	216	9	b.	b.	PROPN
flr-135	216	10	,	,	PUNCT
flr-135	216	11	detienne	detienne	PROPN
flr-135	216	12	d.	d.	PROPN
flr-135	216	13	h.	h.	PROPN
flr-135	216	14	,	,	PUNCT
flr-135	216	15	&	&	CCONJ
flr-135	216	16	joshi	joshi	PROPN
flr-135	216	17	,	,	PUNCT
flr-135	216	18	s.	s.	PROPN
flr-135	216	19	a.	a.	PROPN
flr-135	216	20	(	(	PUNCT
flr-135	216	21	2003	2003	NUM
flr-135	216	22	)	)	PUNCT
flr-135	216	23	.	.	PUNCT
flr-135	217	1	neural	neural	ADJ
flr-135	217	2	networks	network	NOUN
flr-135	217	3	as	as	ADP
flr-135	217	4	statistical	statistical	ADJ
flr-135	217	5	tools	tool	NOUN
flr-135	217	6	for	for	ADP
flr-135	217	7	business	business	NOUN
flr-135	217	8	researchers	researcher	NOUN
flr-135	217	9	.	.	PUNCT
flr-135	218	1	organizational	organizational	ADJ
flr-135	218	2	research	research	NOUN
flr-135	218	3	methods	method	NOUN
flr-135	218	4	,	,	PUNCT
flr-135	218	5	6	6	NUM
flr-135	218	6	,	,	PUNCT
flr-135	218	7	236	236	NUM
flr-135	218	8	-	-	SYM
flr-135	218	9	265	265	NUM
flr-135	218	10	.	.	PUNCT
flr-135	219	1	doi	doi	NOUN
flr-135	219	2	:	:	PUNCT
flr-135	219	3	10.1177/1094428103251907	10.1177/1094428103251907	NUM
flr-135	219	4	donaldson	donaldson	PROPN
flr-135	219	5	,	,	PUNCT
flr-135	219	6	r.	r.	PROPN
flr-135	219	7	g.	g.	PROPN
flr-135	219	8	,	,	PUNCT
flr-135	219	9	&	&	CCONJ
flr-135	219	10	kamstra	kamstra	PROPN
flr-135	219	11	,	,	PUNCT
flr-135	219	12	m.	m.	NOUN
flr-135	219	13	(	(	PUNCT
flr-135	219	14	1999	1999	NUM
flr-135	219	15	)	)	PUNCT
flr-135	219	16	.	.	PUNCT
flr-135	220	1	neural	neural	ADJ
flr-135	220	2	network	network	PROPN
flr-135	220	3	forecast	forecast	NOUN
flr-135	220	4	combining	combine	VERB
flr-135	220	5	with	with	ADP
flr-135	220	6	interaction	interaction	NOUN
flr-135	220	7	effects	effect	NOUN
flr-135	220	8	.	.	PUNCT
flr-135	221	1	journal	journal	NOUN
flr-135	221	2	of	of	ADP
flr-135	221	3	the	the	DET
flr-135	221	4	franklin	franklin	PROPN
flr-135	221	5	institute	institute	PROPN
flr-135	221	6	,	,	PUNCT
flr-135	221	7	336b	336b	PROPN
flr-135	221	8	,	,	PUNCT
flr-135	221	9	227	227	NUM
flr-135	221	10	-	-	SYM
flr-135	221	11	236	236	NUM
flr-135	221	12	.	.	PUNCT
flr-135	222	1	doi	doi	NOUN
flr-135	222	2	:	:	PUNCT
flr-135	222	3	10.1016	10.1016	NUM
flr-135	222	4	/	/	SYM
flr-135	222	5	s0016	s0016	PROPN
flr-135	222	6	-	-	PUNCT
flr-135	222	7	0032(98)00018	0032(98)00018	NOUN
flr-135	222	8	-	-	SYM
flr-135	222	9	0	0	NUM
flr-135	222	10	dreiseitl	dreiseitl	PROPN
flr-135	222	11	,	,	PUNCT
flr-135	222	12	s.	s.	PROPN
flr-135	222	13	,	,	PUNCT
flr-135	222	14	&	&	CCONJ
flr-135	222	15	ohno	ohno	PROPN
flr-135	222	16	-	-	PUNCT
flr-135	222	17	machado	machado	PROPN
flr-135	222	18	,	,	PUNCT
flr-135	222	19	l.	l.	PROPN
flr-135	222	20	(	(	PUNCT
flr-135	222	21	2002	2002	NUM
flr-135	222	22	)	)	PUNCT
flr-135	222	23	.	.	PUNCT
flr-135	223	1	logistic	logistic	ADJ
flr-135	223	2	regression	regression	NOUN
flr-135	223	3	and	and	CCONJ
flr-135	223	4	artificial	artificial	ADJ
flr-135	223	5	neural	neural	ADJ
flr-135	223	6	network	network	NOUN
flr-135	223	7	classification	classification	NOUN
flr-135	223	8	models	model	NOUN
flr-135	223	9	:	:	PUNCT
flr-135	223	10	a	a	DET
flr-135	223	11	methodology	methodology	NOUN
flr-135	223	12	review	review	NOUN
flr-135	223	13	.	.	PUNCT
flr-135	224	1	journal	journal	PROPN
flr-135	224	2	of	of	ADP
flr-135	224	3	biomedical	biomedical	ADJ
flr-135	224	4	informatics	informatic	NOUN
flr-135	224	5	,	,	PUNCT
flr-135	224	6	35	35	NUM
flr-135	224	7	,	,	PUNCT
flr-135	224	8	352–359	352–359	NUM
flr-135	224	9	.	.	PUNCT
flr-135	225	1	doi	doi	NOUN
flr-135	225	2	:	:	PUNCT
flr-135	225	3	10.1016	10.1016	NUM
flr-135	225	4	/	/	SYM
flr-135	225	5	s1532	s1532	PROPN
flr-135	225	6	-	-	PUNCT
flr-135	225	7	0464(03)00034	0464(03)00034	NOUN
flr-135	225	8	-	-	PUNCT
flr-135	225	9	0	0	NUM
flr-135	225	10	edelsbrunner	edelsbrunner	NOUN
flr-135	225	11	,	,	PUNCT
flr-135	225	12	p.	p.	NOUN
flr-135	225	13	,	,	PUNCT
flr-135	225	14	&	&	CCONJ
flr-135	225	15	schneider	schneider	PROPN
flr-135	225	16	,	,	PUNCT
flr-135	225	17	m.	m.	NOUN
flr-135	225	18	(	(	PUNCT
flr-135	225	19	2013	2013	NUM
flr-135	225	20	)	)	PUNCT
flr-135	225	21	.	.	PUNCT
flr-135	226	1	modelling	model	VERB
flr-135	226	2	for	for	ADP
flr-135	226	3	prediction	prediction	NOUN
flr-135	226	4	vs.	vs.	ADP
flr-135	226	5	modelling	modelling	NOUN
flr-135	226	6	for	for	ADP
flr-135	226	7	understanding	understanding	NOUN
flr-135	226	8	:	:	PUNCT
flr-135	226	9	commentary	commentary	NOUN
flr-135	226	10	on	on	ADP
flr-135	226	11	musso	musso	PROPN
flr-135	226	12	et	et	PROPN
flr-135	226	13	al	al	PROPN
flr-135	226	14	.	.	PROPN
flr-135	227	1	(	(	PUNCT
flr-135	227	2	2013	2013	NUM
flr-135	227	3	)	)	PUNCT
flr-135	227	4	.	.	PUNCT
flr-135	228	1	frontline	frontline	NOUN
flr-135	228	2	learning	learn	VERB
flr-135	228	3	research	research	NOUN
flr-135	228	4	,	,	PUNCT
flr-135	228	5	2	2	NUM
flr-135	228	6	,	,	PUNCT
flr-135	228	7	99	99	NUM
flr-135	228	8	-	-	SYM
flr-135	228	9	101	101	NUM
flr-135	228	10	.	.	PUNCT
flr-135	229	1	everson	everson	PROPN
flr-135	229	2	,	,	PUNCT
flr-135	229	3	h.	h.	PROPN
flr-135	229	4	t.	t.	PROPN
flr-135	229	5	,	,	PUNCT
flr-135	229	6	chance	chance	NOUN
flr-135	229	7	,	,	PUNCT
flr-135	229	8	d.	d.	PROPN
flr-135	229	9	,	,	PUNCT
flr-135	229	10	&	&	CCONJ
flr-135	229	11	lykins	lykin	NOUN
flr-135	229	12	,	,	PUNCT
flr-135	229	13	s.	s.	PROPN
flr-135	229	14	(	(	PUNCT
flr-135	229	15	1994	1994	NUM
flr-135	229	16	,	,	PUNCT
flr-135	229	17	april	april	PROPN
flr-135	229	18	)	)	PUNCT
flr-135	229	19	.	.	PUNCT
flr-135	230	1	exploring	explore	VERB
flr-135	230	2	the	the	DET
flr-135	230	3	use	use	NOUN
flr-135	230	4	of	of	ADP
flr-135	230	5	artificial	artificial	ADJ
flr-135	230	6	neural	neural	ADJ
flr-135	230	7	networks	network	NOUN
flr-135	230	8	in	in	ADP
flr-135	230	9	educational	educational	ADJ
flr-135	230	10	research	research	NOUN
flr-135	230	11	.	.	PUNCT
flr-135	231	1	paper	paper	NOUN
flr-135	231	2	presented	present	VERB
flr-135	231	3	at	at	ADP
flr-135	231	4	the	the	DET
flr-135	231	5	annual	annual	ADJ
flr-135	231	6	meeting	meeting	NOUN
flr-135	231	7	of	of	ADP
flr-135	231	8	the	the	DET
flr-135	231	9	american	american	PROPN
flr-135	231	10	educational	educational	PROPN
flr-135	231	11	research	research	PROPN
flr-135	231	12	association	association	PROPN
flr-135	231	13	,	,	PUNCT
flr-135	231	14	new	new	PROPN
flr-135	231	15	orleans	orleans	PROPN
flr-135	231	16	,	,	PUNCT
flr-135	231	17	louisiana	louisiana	PROPN
flr-135	231	18	.	.	PUNCT
flr-135	232	1	frey	frey	PROPN
flr-135	232	2	,	,	PUNCT
flr-135	232	3	u.	u.	PROPN
flr-135	232	4	j.	j.	PROPN
flr-135	232	5	,	,	PUNCT
flr-135	232	6	&	&	CCONJ
flr-135	232	7	rusch	rusch	PROPN
flr-135	232	8	,	,	PUNCT
flr-135	232	9	h.	h.	PROPN
flr-135	232	10	(	(	PUNCT
flr-135	232	11	2013	2013	NUM
flr-135	232	12	)	)	PUNCT
flr-135	232	13	.	.	PUNCT
flr-135	233	1	using	use	VERB
flr-135	233	2	artificial	artificial	ADJ
flr-135	233	3	neural	neural	ADJ
flr-135	233	4	networks	network	NOUN
flr-135	233	5	for	for	ADP
flr-135	233	6	the	the	DET
flr-135	233	7	analysis	analysis	NOUN
flr-135	233	8	of	of	ADP
flr-135	233	9	social	social	ADJ
flr-135	233	10	-	-	PUNCT
flr-135	233	11	ecological	ecological	ADJ
flr-135	233	12	systems	system	NOUN
flr-135	233	13	.	.	PUNCT
flr-135	234	1	ecology	ecology	NOUN
flr-135	234	2	and	and	CCONJ
flr-135	234	3	society	society	NOUN
flr-135	234	4	,	,	PUNCT
flr-135	234	5	18	18	NUM
flr-135	234	6	,	,	PUNCT
flr-135	234	7	40.doi:10.5751	40.doi:10.5751	PROPN
flr-135	234	8	/	/	SYM
flr-135	234	9	es-05202	es-05202	PROPN
flr-135	234	10	-	-	PUNCT
flr-135	234	11	180240	180240	NUM
flr-135	234	12	.	.	PUNCT
flr-135	235	1	frigg	frigg	PROPN
flr-135	235	2	,	,	PUNCT
flr-135	235	3	r.	r.	PROPN
flr-135	235	4	&	&	CCONJ
flr-135	235	5	hartmann	hartmann	PROPN
flr-135	235	6	,	,	PUNCT
flr-135	235	7	s.	s.	PROPN
flr-135	235	8	(	(	PUNCT
flr-135	235	9	2006	2006	NUM
flr-135	235	10	)	)	PUNCT
flr-135	235	11	.	.	PUNCT
flr-135	236	1	models	model	NOUN
flr-135	236	2	in	in	ADP
flr-135	236	3	science	science	NOUN
flr-135	236	4	.	.	PUNCT
flr-135	237	1	in	in	ADP
flr-135	237	2	e.	e.	PROPN
flr-135	237	3	n.	n.	PROPN
flr-135	237	4	zalta	zalta	PROPN
flr-135	237	5	(	(	PUNCT
flr-135	237	6	ed	ed	NOUN
flr-135	237	7	.	.	PUNCT
flr-135	237	8	)	)	PUNCT
flr-135	237	9	,	,	PUNCT
flr-135	237	10	the	the	DET
flr-135	237	11	stanford	stanford	PROPN
flr-135	237	12	encyclopaedia	encyclopaedia	PROPN
flr-135	237	13	of	of	ADP
flr-135	237	14	philosophy	philosophy	NOUN
flr-135	237	15	.	.	PUNCT
flr-135	238	1	summer	summer	NOUN
flr-135	238	2	2006	2006	NUM
flr-135	238	3	edition	edition	NOUN
flr-135	238	4	.	.	PUNCT
flr-135	239	1	stanford	stanford	PROPN
flr-135	239	2	,	,	PUNCT
flr-135	239	3	ca	ca	PROPN
flr-135	239	4	:	:	PUNCT
flr-135	239	5	stanford	stanford	PROPN
flr-135	239	6	university	university	PROPN
flr-135	239	7	press	press	PROPN
flr-135	239	8	.	.	PUNCT
flr-135	240	1	garson	garson	PROPN
flr-135	240	2	,	,	PUNCT
flr-135	240	3	g.	g.	PROPN
flr-135	240	4	d.	d.	PROPN
flr-135	240	5	(	(	PUNCT
flr-135	240	6	1991	1991	NUM
flr-135	240	7	)	)	PUNCT
flr-135	240	8	.	.	PUNCT
flr-135	241	1	interpreting	interpret	VERB
flr-135	241	2	neural	neural	ADJ
flr-135	241	3	-	-	PUNCT
flr-135	241	4	network	network	NOUN
flr-135	241	5	connection	connection	NOUN
flr-135	241	6	weights	weight	NOUN
flr-135	241	7	.	.	PUNCT
flr-135	242	1	ai	ai	VERB
flr-135	242	2	expert	expert	NOUN
flr-135	242	3	,	,	PUNCT
flr-135	242	4	6	6	NUM
flr-135	242	5	,	,	PUNCT
flr-135	242	6	47	47	NUM
flr-135	242	7	-	-	SYM
flr-135	242	8	51	51	NUM
flr-135	242	9	.	.	PUNCT
flr-135	243	1	garson	garson	PROPN
flr-135	243	2	,	,	PUNCT
flr-135	243	3	g.	g.	PROPN
flr-135	243	4	d.	d.	PROPN
flr-135	243	5	(	(	PUNCT
flr-135	243	6	1998	1998	NUM
flr-135	243	7	)	)	PUNCT
flr-135	243	8	.	.	PUNCT
flr-135	244	1	neural	neural	ADJ
flr-135	244	2	networks	network	NOUN
flr-135	244	3	.	.	PUNCT
flr-135	245	1	an	an	DET
flr-135	245	2	introductory	introductory	ADJ
flr-135	245	3	guide	guide	NOUN
flr-135	245	4	for	for	ADP
flr-135	245	5	social	social	ADJ
flr-135	245	6	scientists	scientist	NOUN
flr-135	245	7	.	.	PUNCT
flr-135	246	1	london	london	PROPN
flr-135	246	2	:	:	PUNCT
flr-135	246	3	sage	sage	NOUN
flr-135	246	4	publications	publications	PROPN
flr-135	246	5	ltd	ltd	PROPN
flr-135	246	6	.	.	PROPN
flr-135	246	7	gevrey	gevrey	PROPN
flr-135	246	8	,	,	PUNCT
flr-135	246	9	m.	m.	NOUN
flr-135	246	10	,	,	PUNCT
flr-135	246	11	dimopoulos	dimopoulo	NOUN
flr-135	246	12	,	,	PUNCT
flr-135	246	13	i.	i.	PROPN
flr-135	246	14	,	,	PUNCT
flr-135	246	15	&	&	CCONJ
flr-135	246	16	lek	lek	PROPN
flr-135	246	17	,	,	PUNCT
flr-135	246	18	s.	s.	PROPN
flr-135	246	19	(	(	PUNCT
flr-135	246	20	2003	2003	NUM
flr-135	246	21	)	)	PUNCT
flr-135	246	22	.	.	PUNCT
flr-135	247	1	review	review	NOUN
flr-135	247	2	and	and	CCONJ
flr-135	247	3	comparison	comparison	NOUN
flr-135	247	4	of	of	ADP
flr-135	247	5	methods	method	NOUN
flr-135	247	6	to	to	PART
flr-135	247	7	study	study	VERB
flr-135	247	8	the	the	DET
flr-135	247	9	contribution	contribution	NOUN
flr-135	247	10	of	of	ADP
flr-135	247	11	variables	variable	NOUN
flr-135	247	12	in	in	ADP
flr-135	247	13	artificial	artificial	ADJ
flr-135	247	14	neural	neural	ADJ
flr-135	247	15	network	network	NOUN
flr-135	247	16	models	model	NOUN
flr-135	247	17	.	.	PUNCT
flr-135	248	1	ecological	ecological	ADJ
flr-135	248	2	modelling	modelling	NOUN
flr-135	248	3	,	,	PUNCT
flr-135	248	4	160	160	NUM
flr-135	248	5	,	,	PUNCT
flr-135	248	6	249	249	NUM
flr-135	248	7	-	-	SYM
flr-135	248	8	264	264	NUM
flr-135	248	9	.	.	PUNCT
flr-135	249	1	doi	doi	NOUN
flr-135	249	2	:	:	PUNCT
flr-135	249	3	10.1016	10.1016	NUM
flr-135	249	4	/	/	SYM
flr-135	249	5	s0304	s0304	NOUN
flr-135	249	6	-	-	PUNCT
flr-135	249	7	3800(02)00257	3800(02)00257	ADP
flr-135	249	8	-	-	SYM
flr-135	249	9	0	0	NUM
flr-135	249	10	golino	golino	NOUN
flr-135	249	11	,	,	PUNCT
flr-135	249	12	h.	h.	PROPN
flr-135	249	13	f.	f.	PROPN
flr-135	249	14	,	,	PUNCT
flr-135	249	15	&	&	CCONJ
flr-135	249	16	gomes	gome	NOUN
flr-135	249	17	,	,	PUNCT
flr-135	249	18	c.	c.	PROPN
flr-135	249	19	m.	m.	NOUN
flr-135	249	20	(	(	PUNCT
flr-135	249	21	2014	2014	NUM
flr-135	249	22	)	)	PUNCT
flr-135	249	23	.	.	PUNCT
flr-135	250	1	four	four	NUM
flr-135	250	2	machine	machine	NOUN
flr-135	250	3	learning	learn	VERB
flr-135	250	4	methods	method	NOUN
flr-135	250	5	to	to	PART
flr-135	250	6	predict	predict	VERB
flr-135	250	7	academic	academic	ADJ
flr-135	250	8	achievement	achievement	NOUN
flr-135	250	9	of	of	ADP
flr-135	250	10	college	college	NOUN
flr-135	250	11	students	student	NOUN
flr-135	250	12	:	:	PUNCT
flr-135	250	13	a	a	DET
flr-135	250	14	comparison	comparison	NOUN
flr-135	250	15	study	study	NOUN
flr-135	250	16	.	.	PUNCT
flr-135	251	1	manuscript	manuscript	NOUN
flr-135	251	2	submitted	submit	VERB
flr-135	251	3	for	for	ADP
flr-135	251	4	publication	publication	NOUN
flr-135	251	5	.	.	PUNCT
flr-135	252	1	http://dx.doi.org/10.1214/ss/1177010638	http://dx.doi.org/10.1214/ss/1177010638	PROPN
flr-135	252	2	http://dx.doi.org/10.1287/isre.14.2.189.16018	http://dx.doi.org/10.1287/isre.14.2.189.16018	PROPN
flr-135	252	3	http://dx.doi.org/10.1016/j.edurev.2010.02.002	http://dx.doi.org/10.1016/j.edurev.2010.02.002	NOUN
flr-135	252	4	http://dx.doi.org/10.1177/1094428103251907	http://dx.doi.org/10.1177/1094428103251907	NOUN
flr-135	252	5	http://dx.doi.org/10.1016/s0016-0032(98)00018-0	http://dx.doi.org/10.1016/s0016-0032(98)00018-0	VERB
flr-135	252	6	http://dx.doi.org/10.1016/s1532-0464(03)00034-0	http://dx.doi.org/10.1016/s1532-0464(03)00034-0	ADV
flr-135	252	7	http://dx.doi.org/10.1016/s1532-0464(03)00034-0	http://dx.doi.org/10.1016/s1532-0464(03)00034-0	PROPN
flr-135	252	8	http://dx.doi.org/10.1016/s0304-3800(02)00257-0	http://dx.doi.org/10.1016/s0304-3800(02)00257-0	ADV
flr-135	252	9	http://dx.doi.org/10.1016/s0304-3800(02)00257-0	http://dx.doi.org/10.1016/s0304-3800(02)00257-0	ADV
flr-135	252	10	cascallar	cascallar	ADJ
flr-135	253	1	et	et	NOUN
flr-135	253	2	al	al	PROPN
flr-135	253	3	78	78	NUM
flr-135	254	1	|	|	CCONJ
flr-135	254	2	f	f	NOUN
flr-135	254	3	l	l	NOUN
flr-135	254	4	r	r	NOUN
flr-135	254	5	grishman	grishman	NOUN
flr-135	254	6	,	,	PUNCT
flr-135	254	7	r.	r.	PROPN
flr-135	254	8	,	,	PUNCT
flr-135	254	9	&	&	CCONJ
flr-135	254	10	sundheim	sundheim	PROPN
flr-135	254	11	,	,	PUNCT
flr-135	254	12	b.	b.	PROPN
flr-135	254	13	(	(	PUNCT
flr-135	254	14	1996	1996	NUM
flr-135	254	15	)	)	PUNCT
flr-135	254	16	.	.	PUNCT
flr-135	255	1	message	message	NOUN
flr-135	255	2	understanding	understand	VERB
flr-135	255	3	conference	conference	NOUN
flr-135	255	4	6	6	NUM
flr-135	255	5	:	:	PUNCT
flr-135	255	6	a	a	DET
flr-135	255	7	brief	brief	ADJ
flr-135	255	8	history	history	NOUN
flr-135	255	9	.	.	PUNCT
flr-135	256	1	in	in	ADP
flr-135	256	2	:	:	PUNCT
flr-135	256	3	proceedings	proceeding	NOUN
flr-135	256	4	of	of	ADP
flr-135	256	5	the	the	DET
flr-135	256	6	16th	16th	ADJ
flr-135	256	7	international	international	ADJ
flr-135	256	8	conference	conference	NOUN
flr-135	256	9	on	on	ADP
flr-135	256	10	computational	computational	ADJ
flr-135	256	11	linguistics	linguistic	NOUN
flr-135	256	12	(	(	PUNCT
flr-135	256	13	coling	cole	VERB
flr-135	256	14	)	)	PUNCT
flr-135	256	15	,	,	PUNCT
flr-135	256	16	i	i	PRON
flr-135	256	17	,	,	PUNCT
flr-135	256	18	copenhagen	copenhagen	PROPN
flr-135	256	19	,	,	PUNCT
flr-135	256	20	466–471	466–471	NUM
flr-135	256	21	.	.	PUNCT
flr-135	257	1	haenlein	haenlein	PROPN
flr-135	257	2	,	,	PUNCT
flr-135	257	3	m.	m.	NOUN
flr-135	257	4	,	,	PUNCT
flr-135	257	5	&	&	CCONJ
flr-135	257	6	kaplan	kaplan	PROPN
flr-135	257	7	,	,	PUNCT
flr-135	257	8	a.	a.	PROPN
flr-135	257	9	(	(	PUNCT
flr-135	257	10	2004	2004	NUM
flr-135	257	11	)	)	PUNCT
flr-135	257	12	.	.	PUNCT
flr-135	258	1	a	a	DET
flr-135	258	2	beginner	beginner	NOUN
flr-135	258	3	's	's	PART
flr-135	258	4	guide	guide	NOUN
flr-135	258	5	to	to	ADP
flr-135	258	6	partial	partial	ADJ
flr-135	258	7	least	least	ADJ
flr-135	258	8	squares	square	NOUN
flr-135	258	9	analysis	analysis	NOUN
flr-135	258	10	.	.	PUNCT
flr-135	259	1	understanding	understand	VERB
flr-135	259	2	statistics	statistic	NOUN
flr-135	259	3	,	,	PUNCT
flr-135	259	4	3	3	NUM
flr-135	259	5	,	,	PUNCT
flr-135	259	6	283–297	283–297	NUM
flr-135	259	7	.	.	PUNCT
flr-135	260	1	doi	doi	NOUN
flr-135	260	2	:	:	PUNCT
flr-135	260	3	10.1207	10.1207	NUM
flr-135	260	4	/	/	SYM
flr-135	260	5	s15328031us0304_4	s15328031us0304_4	PROPN
flr-135	260	6	hahn	hahn	PROPN
flr-135	260	7	,	,	PUNCT
flr-135	260	8	c.	c.	PROPN
flr-135	260	9	,	,	PUNCT
flr-135	260	10	johnson	johnson	PROPN
flr-135	260	11	,	,	PUNCT
flr-135	260	12	m.	m.	PROPN
flr-135	260	13	d.	d.	PROPN
flr-135	260	14	,	,	PUNCT
flr-135	260	15	herrmann	herrmann	PROPN
flr-135	260	16	,	,	PUNCT
flr-135	260	17	a.	a.	PROPN
flr-135	260	18	,	,	PUNCT
flr-135	260	19	&	&	CCONJ
flr-135	260	20	huber	huber	PROPN
flr-135	260	21	,	,	PUNCT
flr-135	260	22	f.	f.	PROPN
flr-135	260	23	(	(	PUNCT
flr-135	260	24	2002	2002	NUM
flr-135	260	25	)	)	PUNCT
flr-135	260	26	.	.	PUNCT
flr-135	261	1	capturing	capture	VERB
flr-135	261	2	customer	customer	NOUN
flr-135	261	3	heterogeneity	heterogeneity	NOUN
flr-135	261	4	using	use	VERB
flr-135	261	5	a	a	DET
flr-135	261	6	finite	finite	ADJ
flr-135	261	7	mixture	mixture	NOUN
flr-135	261	8	pls	pls	NOUN
flr-135	261	9	approach	approach	NOUN
flr-135	261	10	.	.	PUNCT
flr-135	262	1	schmalenbach	schmalenbach	NOUN
flr-135	262	2	business	business	NOUN
flr-135	262	3	review	review	PROPN
flr-135	262	4	,	,	PUNCT
flr-135	262	5	54	54	NUM
flr-135	262	6	,	,	PUNCT
flr-135	262	7	243269	243269	NUM
flr-135	262	8	.	.	PUNCT
flr-135	263	1	hand	hand	NOUN
flr-135	263	2	,	,	PUNCT
flr-135	263	3	d.	d.	PROPN
flr-135	263	4	,	,	PUNCT
flr-135	263	5	mannila	mannila	PROPN
flr-135	263	6	,	,	PUNCT
flr-135	263	7	h.	h.	PROPN
flr-135	263	8	,	,	PUNCT
flr-135	263	9	&	&	CCONJ
flr-135	263	10	smyth	smyth	PROPN
flr-135	263	11	,	,	PUNCT
flr-135	263	12	p.	p.	NOUN
flr-135	263	13	(	(	PUNCT
flr-135	263	14	2001	2001	NUM
flr-135	263	15	)	)	PUNCT
flr-135	263	16	.	.	PUNCT
flr-135	264	1	principles	principle	NOUN
flr-135	264	2	of	of	ADP
flr-135	264	3	data	datum	NOUN
flr-135	264	4	mining	mining	NOUN
flr-135	264	5	.	.	PUNCT
flr-135	265	1	cambridge	cambridge	PROPN
flr-135	265	2	,	,	PUNCT
flr-135	265	3	ma	ma	PROPN
flr-135	265	4	:	:	PUNCT
flr-135	265	5	mit	mit	PROPN
flr-135	265	6	press	press	NOUN
flr-135	265	7	.	.	PUNCT
flr-135	266	1	haykin	haykin	PROPN
flr-135	266	2	,	,	PUNCT
flr-135	266	3	s.	s.	PROPN
flr-135	266	4	(	(	PUNCT
flr-135	266	5	1994	1994	NUM
flr-135	266	6	)	)	PUNCT
flr-135	266	7	.	.	PUNCT
flr-135	267	1	neural	neural	ADJ
flr-135	267	2	networks	network	NOUN
flr-135	267	3	:	:	PUNCT
flr-135	267	4	a	a	DET
flr-135	267	5	comprehensive	comprehensive	ADJ
flr-135	267	6	foundation	foundation	NOUN
flr-135	267	7	.	.	PUNCT
flr-135	268	1	new	new	PROPN
flr-135	268	2	york	york	PROPN
flr-135	268	3	:	:	PUNCT
flr-135	268	4	macmillan	macmillan	PROPN
flr-135	268	5	.	.	PUNCT
flr-135	269	1	he	he	PRON
flr-135	269	2	,	,	PUNCT
flr-135	269	3	s.	s.	PROPN
flr-135	269	4	,	,	PUNCT
flr-135	269	5	&	&	CCONJ
flr-135	269	6	li	li	PROPN
flr-135	269	7	,	,	PUNCT
flr-135	269	8	j.	j.	PROPN
flr-135	269	9	(	(	PUNCT
flr-135	269	10	2011	2011	NUM
flr-135	269	11	)	)	PUNCT
flr-135	269	12	.	.	PUNCT
flr-135	270	1	confidence	confidence	NOUN
flr-135	270	2	intervals	interval	NOUN
flr-135	270	3	for	for	ADP
flr-135	270	4	neural	neural	ADJ
flr-135	270	5	networks	network	NOUN
flr-135	270	6	and	and	CCONJ
flr-135	270	7	applications	application	NOUN
flr-135	270	8	to	to	ADP
flr-135	270	9	modeling	model	VERB
flr-135	270	10	engineering	engineering	NOUN
flr-135	270	11	materials	material	NOUN
flr-135	270	12	.	.	PUNCT
flr-135	271	1	in	in	ADP
flr-135	271	2	c.	c.	PROPN
flr-135	271	3	l.	l.	PROPN
flr-135	271	4	p.	p.	PROPN
flr-135	271	5	hui	hui	PROPN
flr-135	272	1	(	(	PUNCT
flr-135	272	2	ed	ed	NOUN
flr-135	272	3	.	.	PUNCT
flr-135	272	4	)	)	PUNCT
flr-135	272	5	,	,	PUNCT
flr-135	272	6	artificial	artificial	ADJ
flr-135	272	7	neural	neural	ADJ
flr-135	272	8	networks	network	NOUN
flr-135	272	9	–	–	PUNCT
flr-135	272	10	application	application	NOUN
flr-135	272	11	.	.	PUNCT
flr-135	273	1	shanghai	shanghai	PROPN
flr-135	273	2	,	,	PUNCT
flr-135	273	3	china	china	PROPN
flr-135	273	4	:	:	PUNCT
flr-135	273	5	intech	intech	PROPN
flr-135	273	6	.	.	PUNCT
flr-135	274	1	doi	doi	PROPN
flr-135	274	2	:	:	PUNCT
flr-135	274	3	10.5772/16097	10.5772/16097	NUM
flr-135	274	4	intrator	intrator	NOUN
flr-135	274	5	,	,	PUNCT
flr-135	274	6	o.	o.	PROPN
flr-135	274	7	,	,	PUNCT
flr-135	274	8	&	&	CCONJ
flr-135	274	9	intrator	intrator	PROPN
flr-135	274	10	,	,	PUNCT
flr-135	274	11	n.	n.	NOUN
flr-135	274	12	(	(	PUNCT
flr-135	274	13	2001	2001	NUM
flr-135	274	14	)	)	PUNCT
flr-135	274	15	.	.	PUNCT
flr-135	275	1	interpreting	interpret	VERB
flr-135	275	2	neural	neural	ADJ
flr-135	275	3	-	-	PUNCT
flr-135	275	4	network	network	NOUN
flr-135	275	5	results	result	NOUN
flr-135	275	6	:	:	PUNCT
flr-135	275	7	a	a	DET
flr-135	275	8	simulation	simulation	NOUN
flr-135	275	9	study	study	NOUN
flr-135	275	10	.	.	PUNCT
flr-135	276	1	computational	computational	ADJ
flr-135	276	2	statistics	statistic	NOUN
flr-135	276	3	and	and	CCONJ
flr-135	276	4	data	datum	NOUN
flr-135	276	5	analysis	analysis	NOUN
flr-135	276	6	,	,	PUNCT
flr-135	276	7	37	37	NUM
flr-135	276	8	,	,	PUNCT
flr-135	276	9	373–393	373–393	NUM
flr-135	276	10	.	.	PUNCT
flr-135	277	1	doi	doi	NOUN
flr-135	277	2	:	:	PUNCT
flr-135	277	3	10.1016	10.1016	NUM
flr-135	277	4	/	/	SYM
flr-135	277	5	s0167	s0167	NUM
flr-135	277	6	-	-	PUNCT
flr-135	277	7	9473(01)00016	9473(01)00016	NUM
flr-135	277	8	-	-	PUNCT
flr-135	277	9	0	0	NUM
flr-135	277	10	kim	kim	PROPN
flr-135	277	11	,	,	PUNCT
flr-135	277	12	j.	j.	PROPN
flr-135	277	13	,	,	PUNCT
flr-135	277	14	&	&	CCONJ
flr-135	277	15	ahn	ahn	PROPN
flr-135	277	16	,	,	PUNCT
flr-135	277	17	h.	h.	PROPN
flr-135	277	18	(	(	PUNCT
flr-135	277	19	2009	2009	NUM
flr-135	277	20	)	)	PUNCT
flr-135	277	21	.	.	PUNCT
flr-135	278	1	a	a	DET
flr-135	278	2	new	new	ADJ
flr-135	278	3	perspective	perspective	NOUN
flr-135	278	4	for	for	ADP
flr-135	278	5	neural	neural	ADJ
flr-135	278	6	networks	network	NOUN
flr-135	278	7	:	:	PUNCT
flr-135	278	8	application	application	NOUN
flr-135	278	9	to	to	ADP
flr-135	278	10	a	a	DET
flr-135	278	11	marketing	marketing	NOUN
flr-135	278	12	management	management	NOUN
flr-135	278	13	problem	problem	NOUN
flr-135	278	14	.	.	PUNCT
flr-135	279	1	journal	journal	NOUN
flr-135	279	2	of	of	ADP
flr-135	279	3	information	information	NOUN
flr-135	279	4	science	science	NOUN
flr-135	279	5	and	and	CCONJ
flr-135	279	6	engineering	engineering	NOUN
flr-135	279	7	,	,	PUNCT
flr-135	279	8	25	25	NUM
flr-135	279	9	,	,	PUNCT
flr-135	279	10	1605	1605	NUM
flr-135	279	11	-	-	SYM
flr-135	279	12	1616	1616	NUM
flr-135	279	13	.	.	PUNCT
flr-135	280	1	kyndt	kyndt	PROPN
flr-135	280	2	,	,	PUNCT
flr-135	280	3	e.	e.	PROPN
flr-135	280	4	,	,	PUNCT
flr-135	280	5	musso	musso	PROPN
flr-135	280	6	,	,	PUNCT
flr-135	280	7	m.	m.	NOUN
flr-135	280	8	,	,	PUNCT
flr-135	280	9	cascallar	cascallar	ADJ
flr-135	280	10	,	,	PUNCT
flr-135	280	11	e.	e.	PROPN
flr-135	280	12	,	,	PUNCT
flr-135	280	13	&	&	CCONJ
flr-135	280	14	dochy	dochy	PROPN
flr-135	280	15	,	,	PUNCT
flr-135	280	16	f.	f.	PROPN
flr-135	280	17	(	(	PUNCT
flr-135	280	18	2011	2011	NUM
flr-135	280	19	,	,	PUNCT
flr-135	280	20	august	august	PROPN
flr-135	280	21	)	)	PUNCT
flr-135	280	22	.	.	PUNCT
flr-135	281	1	predicting	predict	VERB
flr-135	281	2	academic	academic	ADJ
flr-135	281	3	performance	performance	NOUN
flr-135	281	4	in	in	ADP
flr-135	281	5	higher	high	ADJ
flr-135	281	6	education	education	NOUN
flr-135	281	7	:	:	PUNCT
flr-135	281	8	role	role	NOUN
flr-135	281	9	of	of	ADP
flr-135	281	10	cognitive	cognitive	ADJ
flr-135	281	11	,	,	PUNCT
flr-135	281	12	learning	learning	NOUN
flr-135	281	13	and	and	CCONJ
flr-135	281	14	motivation	motivation	NOUN
flr-135	281	15	.	.	PUNCT
flr-135	282	1	symposium	symposium	NOUN
flr-135	282	2	conducted	conduct	VERB
flr-135	282	3	at	at	ADP
flr-135	282	4	the	the	DET
flr-135	282	5	14th	14th	ADJ
flr-135	282	6	earli	earli	PROPN
flr-135	282	7	conference	conference	NOUN
flr-135	282	8	,	,	PUNCT
flr-135	282	9	exeter	exeter	PROPN
flr-135	282	10	,	,	PUNCT
flr-135	282	11	uk	uk	PROPN
flr-135	282	12	.	.	PROPN
flr-135	282	13	kyndt	kyndt	PROPN
flr-135	282	14	,	,	PUNCT
flr-135	282	15	e.	e.	PROPN
flr-135	282	16	,	,	PUNCT
flr-135	282	17	musso	musso	PROPN
flr-135	282	18	,	,	PUNCT
flr-135	282	19	m.	m.	NOUN
flr-135	282	20	,	,	PUNCT
flr-135	282	21	cascallar	cascallar	ADJ
flr-135	282	22	,	,	PUNCT
flr-135	282	23	e.	e.	PROPN
flr-135	282	24	,	,	PUNCT
flr-135	282	25	&	&	CCONJ
flr-135	282	26	dochy	dochy	PROPN
flr-135	282	27	,	,	PUNCT
flr-135	282	28	f.	f.	PROPN
flr-135	282	29	(	(	PUNCT
flr-135	282	30	2015	2015	NUM
flr-135	282	31	,	,	PUNCT
flr-135	282	32	in	in	ADP
flr-135	282	33	press	press	NOUN
flr-135	282	34	)	)	PUNCT
flr-135	282	35	.	.	PUNCT
flr-135	283	1	predicting	predict	VERB
flr-135	283	2	academic	academic	ADJ
flr-135	283	3	performance	performance	NOUN
flr-135	283	4	:	:	PUNCT
flr-135	283	5	the	the	DET
flr-135	283	6	role	role	NOUN
flr-135	283	7	of	of	ADP
flr-135	283	8	cognition	cognition	NOUN
flr-135	283	9	,	,	PUNCT
flr-135	283	10	motivation	motivation	NOUN
flr-135	283	11	and	and	CCONJ
flr-135	283	12	learning	learn	VERB
flr-135	283	13	approaches	approach	NOUN
flr-135	283	14	.	.	PUNCT
flr-135	284	1	a	a	DET
flr-135	284	2	neural	neural	ADJ
flr-135	284	3	network	network	NOUN
flr-135	284	4	analysis	analysis	NOUN
flr-135	284	5	.	.	PUNCT
flr-135	285	1	in	in	ADP
flr-135	285	2	v.	v.	ADP
flr-135	285	3	donche	donche	PROPN
flr-135	285	4	&	&	CCONJ
flr-135	285	5	s.	s.	PROPN
flr-135	285	6	de	de	PROPN
flr-135	285	7	maeyer	maeyer	PROPN
flr-135	285	8	(	(	PUNCT
flr-135	285	9	eds	eds	PROPN
flr-135	285	10	.	.	PUNCT
flr-135	285	11	)	)	PUNCT
flr-135	285	12	,	,	PUNCT
flr-135	285	13	methodological	methodological	ADJ
flr-135	285	14	challenges	challenge	NOUN
flr-135	285	15	in	in	ADP
flr-135	285	16	research	research	NOUN
flr-135	285	17	on	on	ADP
flr-135	285	18	student	student	NOUN
flr-135	285	19	learning	learning	NOUN
flr-135	285	20	.	.	PUNCT
flr-135	286	1	antwerp	antwerp	PROPN
flr-135	286	2	,	,	PUNCT
flr-135	286	3	belgium	belgium	PROPN
flr-135	286	4	:	:	PUNCT
flr-135	286	5	garant	garant	PROPN
flr-135	286	6	.	.	PUNCT
flr-135	287	1	laguna	laguna	PROPN
flr-135	287	2	,	,	PUNCT
flr-135	287	3	m.	m.	NOUN
flr-135	287	4	,	,	PUNCT
flr-135	287	5	&	&	CCONJ
flr-135	287	6	marti	marti	PROPN
flr-135	287	7	,	,	PUNCT
flr-135	287	8	r.	r.	PROPN
flr-135	287	9	(	(	PUNCT
flr-135	287	10	2002	2002	NUM
flr-135	287	11	)	)	PUNCT
flr-135	287	12	.	.	PUNCT
flr-135	288	1	neural	neural	ADJ
flr-135	288	2	network	network	NOUN
flr-135	288	3	prediction	prediction	NOUN
flr-135	288	4	in	in	ADP
flr-135	288	5	a	a	DET
flr-135	288	6	system	system	NOUN
flr-135	288	7	for	for	ADP
flr-135	288	8	optimizing	optimize	VERB
flr-135	288	9	simulations	simulation	NOUN
flr-135	288	10	.	.	PUNCT
flr-135	289	1	iie	iie	NOUN
flr-135	289	2	transactions	transaction	NOUN
flr-135	289	3	,	,	PUNCT
flr-135	289	4	34	34	NUM
flr-135	289	5	,	,	PUNCT
flr-135	289	6	273	273	NUM
flr-135	289	7	-	-	SYM
flr-135	289	8	282	282	NUM
flr-135	289	9	.	.	PUNCT
flr-135	290	1	doi	doi	NOUN
flr-135	290	2	:	:	PUNCT
flr-135	290	3	10.1080/07408170208928869	10.1080/07408170208928869	NUM
flr-135	290	4	lee	lee	PROPN
flr-135	290	5	,	,	PUNCT
flr-135	290	6	c.	c.	PROPN
flr-135	290	7	,	,	PUNCT
flr-135	290	8	rey	rey	PROPN
flr-135	290	9	,	,	PUNCT
flr-135	290	10	t.	t.	PROPN
flr-135	290	11	,	,	PUNCT
flr-135	290	12	mentele	mentele	PROPN
flr-135	290	13	,	,	PUNCT
flr-135	290	14	j.	j.	PROPN
flr-135	290	15	,	,	PUNCT
flr-135	290	16	&	&	CCONJ
flr-135	290	17	garver	garver	NOUN
flr-135	290	18	,	,	PUNCT
flr-135	290	19	m.	m.	NOUN
flr-135	290	20	(	(	PUNCT
flr-135	290	21	2005	2005	NUM
flr-135	290	22	)	)	PUNCT
flr-135	290	23	.	.	PUNCT
flr-135	291	1	structured	structured	ADJ
flr-135	291	2	neural	neural	ADJ
flr-135	291	3	network	network	NOUN
flr-135	291	4	techniques	technique	NOUN
flr-135	291	5	for	for	ADP
flr-135	291	6	modeling	model	VERB
flr-135	291	7	loyalty	loyalty	NOUN
flr-135	291	8	and	and	CCONJ
flr-135	291	9	profitability	profitability	NOUN
flr-135	291	10	.	.	PUNCT
flr-135	292	1	proceedings	proceeding	NOUN
flr-135	292	2	of	of	ADP
flr-135	292	3	the	the	DET
flr-135	292	4	thirtieth	thirtieth	ADJ
flr-135	292	5	annual	annual	ADJ
flr-135	292	6	sas	sa	NOUN
flr-135	292	7	®	®	NOUN
flr-135	292	8	users	user	NOUN
flr-135	292	9	group	group	PROPN
flr-135	292	10	international	international	ADJ
flr-135	292	11	conference	conference	PROPN
flr-135	292	12	.	.	PUNCT
flr-135	293	1	cary	cary	PROPN
flr-135	293	2	,	,	PUNCT
flr-135	293	3	nc	nc	PROPN
flr-135	293	4	:	:	PROPN
flr-135	293	5	sas	sas	PROPN
flr-135	293	6	institute	institute	PROPN
flr-135	293	7	inc	inc	PROPN
flr-135	293	8	.	.	PROPN
flr-135	293	9	lei	lei	PROPN
flr-135	293	10	,	,	PUNCT
flr-135	293	11	p.	p.	PROPN
flr-135	293	12	w.	w.	PROPN
flr-135	293	13	,	,	PUNCT
flr-135	293	14	&	&	CCONJ
flr-135	293	15	qiong	qiong	PROPN
flr-135	293	16	wu	wu	PROPN
flr-135	293	17	,	,	PUNCT
flr-135	293	18	q.	q.	PROPN
flr-135	293	19	(	(	PUNCT
flr-135	293	20	2007	2007	NUM
flr-135	293	21	)	)	PUNCT
flr-135	293	22	.	.	PUNCT
flr-135	294	1	introduction	introduction	NOUN
flr-135	294	2	to	to	ADP
flr-135	294	3	structural	structural	ADJ
flr-135	294	4	equation	equation	NOUN
flr-135	294	5	modelling	modelling	NOUN
flr-135	294	6	:	:	PUNCT
flr-135	294	7	issues	issue	NOUN
flr-135	294	8	and	and	CCONJ
flr-135	294	9	practical	practical	ADJ
flr-135	294	10	considerations	consideration	NOUN
flr-135	294	11	.	.	PUNCT
flr-135	295	1	items	item	NOUN
flr-135	295	2	–	–	PUNCT
flr-135	295	3	instructional	instructional	ADJ
flr-135	295	4	topics	topic	NOUN
flr-135	295	5	in	in	ADP
flr-135	295	6	educational	educational	ADJ
flr-135	295	7	measurement	measurement	NOUN
flr-135	295	8	fall	fall	VERB
flr-135	295	9	2007	2007	NUM
flr-135	295	10	,	,	PUNCT
flr-135	295	11	ncme	ncme	PROPN
flr-135	295	12	instructional	instructional	ADJ
flr-135	295	13	module	module	NOUN
flr-135	295	14	,	,	PUNCT
flr-135	295	15	33	33	NUM
flr-135	295	16	-	-	SYM
flr-135	295	17	43	43	NUM
flr-135	295	18	.	.	PUNCT
flr-135	296	1	lek	lek	PROPN
flr-135	296	2	,	,	PUNCT
flr-135	296	3	s.	s.	PROPN
flr-135	296	4	,	,	PUNCT
flr-135	296	5	belaud	belaud	PROPN
flr-135	296	6	,	,	PUNCT
flr-135	296	7	a.	a.	NOUN
flr-135	296	8	,	,	PUNCT
flr-135	296	9	baran	baran	NOUN
flr-135	296	10	,	,	PUNCT
flr-135	296	11	p.	p.	PROPN
flr-135	296	12	,	,	PUNCT
flr-135	296	13	dimopoulos	dimopoulo	NOUN
flr-135	296	14	,	,	PUNCT
flr-135	296	15	i.	i.	PROPN
flr-135	296	16	,	,	PUNCT
flr-135	296	17	&	&	CCONJ
flr-135	296	18	delacoste	delacoste	NOUN
flr-135	296	19	,	,	PUNCT
flr-135	296	20	m.	m.	NOUN
flr-135	296	21	(	(	PUNCT
flr-135	296	22	1996	1996	NUM
flr-135	296	23	)	)	PUNCT
flr-135	296	24	.	.	PUNCT
flr-135	297	1	role	role	NOUN
flr-135	297	2	of	of	ADP
flr-135	297	3	some	some	DET
flr-135	297	4	environmental	environmental	ADJ
flr-135	297	5	variables	variable	NOUN
flr-135	297	6	in	in	ADP
flr-135	297	7	trout	trout	NOUN
flr-135	297	8	abundance	abundance	NOUN
flr-135	297	9	models	model	NOUN
flr-135	297	10	using	use	VERB
flr-135	297	11	neural	neural	ADJ
flr-135	297	12	networks	network	NOUN
flr-135	297	13	.	.	PUNCT
flr-135	298	1	aquat	aquat	VERB
flr-135	298	2	.	.	PUNCT
flr-135	299	1	living	live	VERB
flr-135	299	2	resour	resour	NOUN
flr-135	299	3	,	,	PUNCT
flr-135	299	4	9	9	NUM
flr-135	299	5	,	,	PUNCT
flr-135	299	6	23	23	NUM
flr-135	299	7	-	-	SYM
flr-135	299	8	29	29	NUM
flr-135	299	9	.	.	PUNCT
flr-135	300	1	doi	doi	NOUN
flr-135	300	2	:	:	PUNCT
flr-135	300	3	10.1051	10.1051	NUM
flr-135	300	4	/	/	SYM
flr-135	300	5	alr:1996004	alr:1996004	ADJ
flr-135	300	6	http://dx.doi.org/10.1207/s15328031us0304_4	http://dx.doi.org/10.1207/s15328031us0304_4	NOUN
flr-135	301	1	http://dx.doi.org/10.5772/16097	http://dx.doi.org/10.5772/16097	PROPN
flr-135	302	1	http://dx.doi.org/10.1016/s0167-9473(01)00016-0	http://dx.doi.org/10.1016/s0167-9473(01)00016-0	ADJ
flr-135	302	2	http://dx.doi.org/10.1080/07408170208928869	http://dx.doi.org/10.1080/07408170208928869	NOUN
flr-135	302	3	http://dx.doi.org/10.1051/alr:1996004	http://dx.doi.org/10.1051/alr:1996004	VERB
flr-135	302	4	http://dx.doi.org/10.1051/alr:1996004	http://dx.doi.org/10.1051/alr:1996004	PUNCT
flr-135	302	5	cascallar	cascallar	NOUN
flr-135	302	6	et	et	PROPN
flr-135	302	7	al	al	PROPN
flr-135	302	8	79	79	NUM
flr-135	303	1	|	|	NOUN
flr-135	303	2	f	f	NOUN
flr-135	303	3	l	l	NOUN
flr-135	303	4	r	r	NOUN
flr-135	303	5	luft	luft	NOUN
flr-135	303	6	,	,	PUNCT
flr-135	303	7	c.	c.	PROPN
flr-135	303	8	d.	d.	PROPN
flr-135	303	9	b.	b.	PROPN
flr-135	303	10	,	,	PUNCT
flr-135	303	11	gomes	gomes	PROPN
flr-135	303	12	,	,	PUNCT
flr-135	303	13	j.	j.	PROPN
flr-135	303	14	s.	s.	PROPN
flr-135	303	15	,	,	PUNCT
flr-135	303	16	priori	priori	ADV
flr-135	303	17	,	,	PUNCT
flr-135	303	18	d.	d.	PROPN
flr-135	303	19	,	,	PUNCT
flr-135	303	20	&	&	CCONJ
flr-135	303	21	takase	takase	PROPN
flr-135	303	22	,	,	PUNCT
flr-135	303	23	e.	e.	PROPN
flr-135	303	24	(	(	PUNCT
flr-135	303	25	2013	2013	NUM
flr-135	303	26	)	)	PUNCT
flr-135	303	27	.	.	PUNCT
flr-135	304	1	using	use	VERB
flr-135	304	2	online	online	ADJ
flr-135	304	3	cognitive	cognitive	ADJ
flr-135	304	4	tasks	task	NOUN
flr-135	304	5	to	to	PART
flr-135	304	6	predict	predict	VERB
flr-135	304	7	mathematics	mathematics	PROPN
flr-135	304	8	low	low	ADJ
flr-135	304	9	school	school	NOUN
flr-135	304	10	achievement	achievement	NOUN
flr-135	304	11	.	.	PUNCT
flr-135	305	1	computers	computer	NOUN
flr-135	305	2	&	&	CCONJ
flr-135	305	3	education	education	PROPN
flr-135	305	4	,	,	PUNCT
flr-135	305	5	67	67	NUM
flr-135	305	6	,	,	PUNCT
flr-135	305	7	219	219	NUM
flr-135	305	8	-	-	SYM
flr-135	305	9	228	228	NUM
flr-135	305	10	.	.	PUNCT
flr-135	306	1	doi	doi	NOUN
flr-135	306	2	:	:	PUNCT
flr-135	306	3	10.1016	10.1016	NUM
flr-135	306	4	/	/	SYM
flr-135	306	5	j.compedu.2013.04.001	j.compedu.2013.04.001	PROPN
flr-135	306	6	mackay	mackay	PROPN
flr-135	306	7	,	,	PUNCT
flr-135	306	8	d.	d.	PROPN
flr-135	306	9	j.	j.	PROPN
flr-135	306	10	c.	c.	PROPN
flr-135	306	11	(	(	PUNCT
flr-135	306	12	1992	1992	NUM
flr-135	306	13	)	)	PUNCT
flr-135	306	14	.	.	PUNCT
flr-135	307	1	a	a	DET
flr-135	307	2	practical	practical	ADJ
flr-135	307	3	bayesian	bayesian	NOUN
flr-135	307	4	framework	framework	NOUN
flr-135	307	5	for	for	ADP
flr-135	307	6	backpropagation	backpropagation	NOUN
flr-135	307	7	networks	network	NOUN
flr-135	307	8	.	.	PUNCT
flr-135	308	1	neural	neural	ADJ
flr-135	308	2	computation	computation	NOUN
flr-135	308	3	,	,	PUNCT
flr-135	308	4	4	4	NUM
flr-135	308	5	,	,	PUNCT
flr-135	308	6	448472	448472	NUM
flr-135	308	7	.	.	PUNCT
flr-135	309	1	doi	doi	NOUN
flr-135	309	2	:	:	PUNCT
flr-135	309	3	10.1162	10.1162	NUM
flr-135	309	4	/	/	SYM
flr-135	309	5	neco.1992.4.3.448	neco.1992.4.3.448	PROPN
flr-135	309	6	marquez	marquez	PROPN
flr-135	309	7	,	,	PUNCT
flr-135	309	8	l.	l.	PROPN
flr-135	309	9	,	,	PUNCT
flr-135	309	10	hill	hill	PROPN
flr-135	309	11	,	,	PUNCT
flr-135	309	12	t.	t.	PROPN
flr-135	309	13	,	,	PUNCT
flr-135	309	14	worthley	worthley	PROPN
flr-135	309	15	,	,	PUNCT
flr-135	309	16	r.	r.	PROPN
flr-135	309	17	,	,	PUNCT
flr-135	309	18	&	&	CCONJ
flr-135	309	19	remus	remus	PROPN
flr-135	309	20	,	,	PUNCT
flr-135	309	21	w.	w.	PROPN
flr-135	309	22	(	(	PUNCT
flr-135	309	23	1991	1991	NUM
flr-135	309	24	)	)	PUNCT
flr-135	309	25	.	.	PUNCT
flr-135	310	1	neural	neural	ADJ
flr-135	310	2	network	network	NOUN
flr-135	310	3	models	model	NOUN
flr-135	310	4	as	as	ADP
flr-135	310	5	an	an	DET
flr-135	310	6	alternative	alternative	NOUN
flr-135	310	7	to	to	AUX
flr-135	310	8	regression	regression	NOUN
flr-135	310	9	.	.	PUNCT
flr-135	311	1	proceedings	proceeding	NOUN
flr-135	311	2	of	of	ADP
flr-135	311	3	the	the	DET
flr-135	311	4	ieee	ieee	NOUN
flr-135	311	5	24th	24th	NOUN
flr-135	311	6	annual	annual	ADJ
flr-135	311	7	hawaii	hawaii	PROPN
flr-135	311	8	international	international	PROPN
flr-135	311	9	conference	conference	NOUN
flr-135	311	10	on	on	ADP
flr-135	311	11	systems	system	NOUN
flr-135	311	12	sciences	science	NOUN
flr-135	311	13	,	,	PUNCT
flr-135	311	14	4	4	NUM
flr-135	311	15	,	,	PUNCT
flr-135	311	16	129	129	NUM
flr-135	311	17	-	-	SYM
flr-135	311	18	135	135	NUM
flr-135	311	19	.	.	PUNCT
flr-135	312	1	doi	doi	NOUN
flr-135	312	2	:	:	PUNCT
flr-135	312	3	10.1109	10.1109	NUM
flr-135	312	4	/	/	SYM
flr-135	312	5	hicss.1991.184052	hicss.1991.184052	PROPN
flr-135	312	6	monteith	monteith	PROPN
flr-135	312	7	,	,	PUNCT
flr-135	312	8	k.	k.	PROPN
flr-135	312	9	,	,	PUNCT
flr-135	312	10	carroll	carroll	PROPN
flr-135	312	11	,	,	PUNCT
flr-135	312	12	j.	j.	PROPN
flr-135	312	13	,	,	PUNCT
flr-135	312	14	seppi	seppi	PROPN
flr-135	312	15	,	,	PUNCT
flr-135	312	16	k.	k.	PROPN
flr-135	312	17	,	,	PUNCT
flr-135	312	18	&	&	CCONJ
flr-135	312	19	martinez	martinez	PROPN
flr-135	312	20	,	,	PUNCT
flr-135	312	21	t.	t.	PROPN
flr-135	312	22	(	(	PUNCT
flr-135	312	23	2011	2011	NUM
flr-135	312	24	)	)	PUNCT
flr-135	312	25	.	.	PUNCT
flr-135	313	1	turning	turn	VERB
flr-135	313	2	bayesian	bayesian	NOUN
flr-135	313	3	model	model	NOUN
flr-135	313	4	averaging	average	VERB
flr-135	313	5	into	into	ADP
flr-135	313	6	bayesian	bayesian	NOUN
flr-135	313	7	model	model	NOUN
flr-135	313	8	combination	combination	NOUN
flr-135	313	9	.	.	PUNCT
flr-135	314	1	in	in	ADP
flr-135	314	2	:	:	PUNCT
flr-135	314	3	proceedings	proceeding	NOUN
flr-135	314	4	of	of	ADP
flr-135	314	5	the	the	DET
flr-135	314	6	international	international	ADJ
flr-135	314	7	joint	joint	ADJ
flr-135	314	8	conference	conference	NOUN
flr-135	314	9	on	on	ADP
flr-135	314	10	neural	neural	ADJ
flr-135	314	11	networks	network	NOUN
flr-135	314	12	(	(	PUNCT
flr-135	314	13	ijcnn	ijcnn	PROPN
flr-135	314	14	)	)	PUNCT
flr-135	314	15	2011	2011	NUM
flr-135	314	16	,	,	PUNCT
flr-135	314	17	2657–2663	2657–2663	NUM
flr-135	314	18	.	.	PUNCT
flr-135	314	19	musso	musso	PROPN
flr-135	314	20	,	,	PUNCT
flr-135	314	21	m.	m.	PROPN
flr-135	314	22	f.	f.	PROPN
flr-135	314	23	,	,	PUNCT
flr-135	314	24	&	&	CCONJ
flr-135	314	25	cascallar	cascallar	PROPN
flr-135	314	26	,	,	PUNCT
flr-135	314	27	e.	e.	PROPN
flr-135	314	28	c.	c.	PROPN
flr-135	314	29	(	(	PUNCT
flr-135	314	30	2009a	2009a	NUM
flr-135	314	31	)	)	PUNCT
flr-135	314	32	.	.	PUNCT
flr-135	315	1	new	new	ADJ
flr-135	315	2	approaches	approach	NOUN
flr-135	315	3	for	for	ADP
flr-135	315	4	improved	improved	ADJ
flr-135	315	5	quality	quality	NOUN
flr-135	315	6	in	in	ADP
flr-135	315	7	educational	educational	ADJ
flr-135	315	8	assessments	assessment	NOUN
flr-135	315	9	:	:	PUNCT
flr-135	315	10	using	use	VERB
flr-135	315	11	automated	automate	VERB
flr-135	315	12	predictive	predictive	ADJ
flr-135	315	13	systems	system	NOUN
flr-135	315	14	in	in	ADP
flr-135	315	15	reading	reading	NOUN
flr-135	315	16	and	and	CCONJ
flr-135	315	17	mathematics	mathematic	NOUN
flr-135	315	18	.	.	PUNCT
flr-135	316	1	journal	journal	PROPN
flr-135	316	2	of	of	ADP
flr-135	316	3	problems	problem	NOUN
flr-135	316	4	of	of	ADP
flr-135	316	5	education	education	NOUN
flr-135	316	6	in	in	ADP
flr-135	316	7	the	the	DET
flr-135	316	8	21st	21st	ADJ
flr-135	316	9	century	century	NOUN
flr-135	316	10	,	,	PUNCT
flr-135	316	11	17	17	NUM
flr-135	316	12	,	,	PUNCT
flr-135	316	13	134	134	NUM
flr-135	316	14	-	-	SYM
flr-135	316	15	151	151	NUM
flr-135	316	16	.	.	PUNCT
flr-135	317	1	musso	musso	PROPN
flr-135	317	2	,	,	PUNCT
flr-135	317	3	m.	m.	PROPN
flr-135	317	4	f.	f.	PROPN
flr-135	317	5	&	&	CCONJ
flr-135	317	6	cascallar	cascallar	PROPN
flr-135	317	7	,	,	PUNCT
flr-135	317	8	e.	e.	PROPN
flr-135	317	9	c.	c.	PROPN
flr-135	317	10	(	(	PUNCT
flr-135	317	11	2009b).predictive	2009b).predictive	ADJ
flr-135	317	12	systems	system	NOUN
flr-135	317	13	using	use	VERB
flr-135	317	14	artificial	artificial	ADJ
flr-135	317	15	neural	neural	ADJ
flr-135	317	16	networks	network	NOUN
flr-135	317	17	:	:	PUNCT
flr-135	317	18	an	an	DET
flr-135	317	19	introduction	introduction	NOUN
flr-135	317	20	to	to	ADP
flr-135	317	21	concepts	concept	NOUN
flr-135	317	22	and	and	CCONJ
flr-135	317	23	applications	application	NOUN
flr-135	317	24	in	in	ADP
flr-135	317	25	education	education	NOUN
flr-135	317	26	and	and	CCONJ
flr-135	317	27	social	social	ADJ
flr-135	317	28	sciences	science	NOUN
flr-135	317	29	.	.	PUNCT
flr-135	318	1	in	in	ADP
flr-135	318	2	m.	m.	PROPN
flr-135	318	3	c.	c.	PROPN
flr-135	318	4	richaud	richaud	PROPN
flr-135	318	5	&	&	CCONJ
flr-135	318	6	j.	j.	PROPN
flr-135	318	7	e.	e.	PROPN
flr-135	318	8	moreno	moreno	PROPN
flr-135	318	9	(	(	PUNCT
flr-135	318	10	eds	eds	PROPN
flr-135	318	11	.	.	PUNCT
flr-135	318	12	)	)	PUNCT
flr-135	318	13	.	.	PUNCT
flr-135	319	1	research	research	NOUN
flr-135	319	2	in	in	ADP
flr-135	319	3	behavioural	behavioural	ADJ
flr-135	319	4	sciences	science	NOUN
flr-135	319	5	(	(	PUNCT
flr-135	319	6	volume	volume	NOUN
flr-135	319	7	i	i	PROPN
flr-135	319	8	)	)	PUNCT
flr-135	319	9	,	,	PUNCT
flr-135	319	10	(	(	PUNCT
flr-135	319	11	pp	pp	X
flr-135	319	12	.	.	PUNCT
flr-135	320	1	433	433	NUM
flr-135	320	2	-	-	NUM
flr-135	320	3	459	459	NUM
flr-135	320	4	)	)	PUNCT
flr-135	320	5	.	.	PUNCT
flr-135	321	1	buenos	buenos	PROPN
flr-135	321	2	aires	aires	PROPN
flr-135	321	3	,	,	PUNCT
flr-135	321	4	argentina	argentina	PROPN
flr-135	321	5	:	:	PUNCT
flr-135	321	6	ciipme	ciipme	NOUN
flr-135	321	7	/	/	SYM
flr-135	321	8	conicet	conicet	PROPN
flr-135	321	9	.	.	PUNCT
flr-135	321	10	musso	musso	PROPN
flr-135	321	11	,	,	PUNCT
flr-135	321	12	m.	m.	PROPN
flr-135	321	13	f.	f.	PROPN
flr-135	321	14	,	,	PUNCT
flr-135	321	15	kyndt	kyndt	PROPN
flr-135	321	16	,	,	PUNCT
flr-135	321	17	e.	e.	PROPN
flr-135	321	18	,	,	PUNCT
flr-135	321	19	cascallar	cascallar	PROPN
flr-135	321	20	,	,	PUNCT
flr-135	321	21	e.	e.	PROPN
flr-135	321	22	c.	c.	PROPN
flr-135	321	23	,	,	PUNCT
flr-135	321	24	&	&	CCONJ
flr-135	321	25	dochy	dochy	PROPN
flr-135	321	26	,	,	PUNCT
flr-135	321	27	f.	f.	PROPN
flr-135	321	28	(	(	PUNCT
flr-135	321	29	2012	2012	NUM
flr-135	321	30	)	)	PUNCT
flr-135	321	31	.	.	PUNCT
flr-135	322	1	predicting	predict	VERB
flr-135	322	2	mathematical	mathematical	ADJ
flr-135	322	3	performance	performance	NOUN
flr-135	322	4	:	:	PUNCT
flr-135	322	5	the	the	DET
flr-135	322	6	effect	effect	NOUN
flr-135	322	7	of	of	ADP
flr-135	322	8	cognitive	cognitive	ADJ
flr-135	322	9	processes	process	NOUN
flr-135	322	10	and	and	CCONJ
flr-135	322	11	self	self	NOUN
flr-135	322	12	-	-	PUNCT
flr-135	322	13	regulation	regulation	NOUN
flr-135	322	14	factors	factor	NOUN
flr-135	322	15	.	.	PUNCT
flr-135	323	1	education	education	NOUN
flr-135	323	2	research	research	PROPN
flr-135	323	3	international	international	PROPN
flr-135	323	4	.	.	PUNCT
flr-135	324	1	vol	vol	NOUN
flr-135	324	2	2012	2012	NUM
flr-135	324	3	,	,	PUNCT
flr-135	324	4	article	article	NOUN
flr-135	324	5	i	i	PROPN
flr-135	324	6	d	d	PROPN
flr-135	324	7	250719	250719	NUM
flr-135	324	8	,	,	PUNCT
flr-135	324	9	13	13	NUM
flr-135	324	10	pages	page	NOUN
flr-135	324	11	.	.	PUNCT
flr-135	325	1	doi	doi	NOUN
flr-135	325	2	:	:	PUNCT
flr-135	325	3	10.1155/2012/250719	10.1155/2012/250719	NUM
flr-135	325	4	musso	musso	NOUN
flr-135	325	5	,	,	PUNCT
flr-135	325	6	m.	m.	PROPN
flr-135	325	7	f.	f.	PROPN
flr-135	325	8	,	,	PUNCT
flr-135	325	9	kyndt	kyndt	PROPN
flr-135	325	10	,	,	PUNCT
flr-135	325	11	e.	e.	PROPN
flr-135	325	12	,	,	PUNCT
flr-135	325	13	cascallar	cascallar	PROPN
flr-135	325	14	,	,	PUNCT
flr-135	325	15	e.	e.	PROPN
flr-135	325	16	c.	c.	PROPN
flr-135	325	17	,	,	PUNCT
flr-135	325	18	&	&	CCONJ
flr-135	325	19	dochy	dochy	PROPN
flr-135	325	20	,	,	PUNCT
flr-135	325	21	f.	f.	PROPN
flr-135	325	22	(	(	PUNCT
flr-135	325	23	2013	2013	NUM
flr-135	325	24	)	)	PUNCT
flr-135	325	25	.	.	PUNCT
flr-135	326	1	predicting	predict	VERB
flr-135	326	2	general	general	ADJ
flr-135	326	3	academic	academic	ADJ
flr-135	326	4	performance	performance	NOUN
flr-135	326	5	and	and	CCONJ
flr-135	326	6	identifying	identify	VERB
flr-135	326	7	differential	differential	ADJ
flr-135	326	8	contribution	contribution	NOUN
flr-135	326	9	of	of	ADP
flr-135	326	10	participating	participate	VERB
flr-135	326	11	variables	variable	NOUN
flr-135	326	12	using	use	VERB
flr-135	326	13	artificial	artificial	ADJ
flr-135	326	14	neural	neural	ADJ
flr-135	326	15	networks	network	NOUN
flr-135	326	16	.	.	PUNCT
flr-135	327	1	frontline	frontline	NOUN
flr-135	327	2	learning	learn	VERB
flr-135	327	3	research	research	NOUN
flr-135	327	4	,	,	PUNCT
flr-135	327	5	1	1	NUM
flr-135	327	6	,	,	PUNCT
flr-135	327	7	42	42	NUM
flr-135	327	8	-	-	SYM
flr-135	327	9	71	71	NUM
flr-135	327	10	.	.	PUNCT
flr-135	327	11	doi	doi	NOUN
flr-135	327	12	:	:	PUNCT
flr-135	327	13	10.14786	10.14786	NUM
flr-135	327	14	/	/	SYM
flr-135	327	15	flr.v1i1.13	flr.v1i1.13	PROPN
flr-135	327	16	musso	musso	PROPN
flr-135	327	17	,	,	PUNCT
flr-135	327	18	m.	m.	PROPN
flr-135	327	19	f.	f.	PROPN
flr-135	327	20	,	,	PUNCT
flr-135	327	21	boekaerts	boekaert	NOUN
flr-135	327	22	,	,	PUNCT
flr-135	327	23	m.	m.	NOUN
flr-135	327	24	,	,	PUNCT
flr-135	327	25	segers	seger	NOUN
flr-135	327	26	,	,	PUNCT
flr-135	327	27	m.	m.	NOUN
flr-135	327	28	,	,	PUNCT
flr-135	327	29	&	&	CCONJ
flr-135	327	30	cascallar	cascallar	PROPN
flr-135	327	31	,	,	PUNCT
flr-135	327	32	e.	e.	PROPN
flr-135	327	33	c.	c.	PROPN
flr-135	327	34	(	(	PUNCT
flr-135	327	35	in	in	ADP
flr-135	327	36	preparation	preparation	NOUN
flr-135	327	37	)	)	PUNCT
flr-135	327	38	.	.	PUNCT
flr-135	328	1	a	a	DET
flr-135	328	2	comparative	comparative	ADJ
flr-135	328	3	analysis	analysis	NOUN
flr-135	328	4	of	of	ADP
flr-135	328	5	the	the	DET
flr-135	328	6	prediction	prediction	NOUN
flr-135	328	7	of	of	ADP
flr-135	328	8	student	student	NOUN
flr-135	328	9	academic	academic	ADJ
flr-135	328	10	performance	performance	NOUN
flr-135	328	11	.	.	PUNCT
flr-135	329	1	neal	neal	PROPN
flr-135	329	2	,	,	PUNCT
flr-135	329	3	w.	w.	PROPN
flr-135	329	4	,	,	PUNCT
flr-135	329	5	&	&	CCONJ
flr-135	329	6	wurst	wurst	PROPN
flr-135	329	7	,	,	PUNCT
flr-135	329	8	j.	j.	PROPN
flr-135	329	9	(	(	PUNCT
flr-135	329	10	2001	2001	NUM
flr-135	329	11	)	)	PUNCT
flr-135	329	12	.	.	PUNCT
flr-135	330	1	advances	advance	NOUN
flr-135	330	2	in	in	ADP
flr-135	330	3	market	market	NOUN
flr-135	330	4	segmentation	segmentation	NOUN
flr-135	330	5	.	.	PUNCT
flr-135	331	1	marketing	marketing	NOUN
flr-135	331	2	research	research	NOUN
flr-135	331	3	,	,	PUNCT
flr-135	331	4	13	13	NUM
flr-135	331	5	,	,	PUNCT
flr-135	331	6	14	14	NUM
flr-135	331	7	-	-	SYM
flr-135	331	8	18	18	NUM
flr-135	331	9	.	.	PUNCT
flr-135	332	1	nguyen	nguyen	NOUN
flr-135	332	2	,	,	PUNCT
flr-135	332	3	n.	n.	NOUN
flr-135	332	4	,	,	PUNCT
flr-135	332	5	&	&	CCONJ
flr-135	332	6	cripps	cripps	PROPN
flr-135	332	7	,	,	PUNCT
flr-135	332	8	a.	a.	NOUN
flr-135	332	9	(	(	PUNCT
flr-135	332	10	2001	2001	NUM
flr-135	332	11	)	)	PUNCT
flr-135	332	12	.	.	PUNCT
flr-135	333	1	predicting	predict	VERB
flr-135	333	2	housing	housing	NOUN
flr-135	333	3	value	value	NOUN
flr-135	333	4	:	:	PUNCT
flr-135	333	5	a	a	DET
flr-135	333	6	comparison	comparison	NOUN
flr-135	333	7	of	of	ADP
flr-135	333	8	multiple	multiple	ADJ
flr-135	333	9	regression	regression	NOUN
flr-135	333	10	and	and	CCONJ
flr-135	333	11	artificial	artificial	ADJ
flr-135	333	12	neural	neural	ADJ
flr-135	333	13	networks	network	NOUN
flr-135	333	14	.	.	PUNCT
flr-135	334	1	journal	journal	NOUN
flr-135	334	2	of	of	ADP
flr-135	334	3	real	real	ADJ
flr-135	334	4	estate	estate	NOUN
flr-135	334	5	research	research	NOUN
flr-135	334	6	,	,	PUNCT
flr-135	334	7	22	22	NUM
flr-135	334	8	,	,	PUNCT
flr-135	334	9	313	313	NUM
flr-135	334	10	-	-	SYM
flr-135	334	11	336	336	NUM
flr-135	334	12	.	.	PUNCT
flr-135	335	1	nokelainen	nokelainen	NOUN
flr-135	335	2	,	,	PUNCT
flr-135	335	3	p.	p.	NOUN
flr-135	335	4	&	&	CCONJ
flr-135	335	5	silander	silander	NOUN
flr-135	335	6	,	,	PUNCT
flr-135	335	7	t.	t.	PROPN
flr-135	335	8	(	(	PUNCT
flr-135	335	9	2014	2014	NUM
flr-135	335	10	)	)	PUNCT
flr-135	335	11	.	.	PUNCT
flr-135	336	1	using	use	VERB
flr-135	336	2	new	new	ADJ
flr-135	336	3	models	model	NOUN
flr-135	336	4	to	to	PART
flr-135	336	5	analyse	analyse	VERB
flr-135	336	6	true	true	ADJ
flr-135	336	7	complex	complex	ADJ
flr-135	336	8	regularities	regularity	NOUN
flr-135	336	9	of	of	ADP
flr-135	336	10	the	the	DET
flr-135	336	11	world	world	NOUN
flr-135	336	12	:	:	PUNCT
flr-135	336	13	commentary	commentary	NOUN
flr-135	336	14	on	on	ADP
flr-135	336	15	musso	musso	PROPN
flr-135	336	16	et	et	PROPN
flr-135	336	17	al	al	PROPN
flr-135	336	18	.	.	PROPN
flr-135	337	1	(	(	PUNCT
flr-135	337	2	2013	2013	NUM
flr-135	337	3	)	)	PUNCT
flr-135	337	4	.	.	PUNCT
flr-135	338	1	frontiers	frontier	NOUN
flr-135	338	2	in	in	ADP
flr-135	338	3	psychology	psychology	NOUN
flr-135	338	4	,	,	PUNCT
flr-135	338	5	3	3	NUM
flr-135	338	6	,	,	PUNCT
flr-135	338	7	78	78	NUM
flr-135	338	8	-	-	SYM
flr-135	338	9	82	82	NUM
flr-135	338	10	.	.	PUNCT
flr-135	339	1	doi	doi	NOUN
flr-135	339	2	:	:	PUNCT
flr-135	339	3	.org/10.14786	.org/10.14786	PROPN
flr-135	339	4	/	/	SYM
flr-135	339	5	flr.v2i1.107	flr.v2i1.107	PROPN
flr-135	339	6	.	.	PUNCT
flr-135	340	1	olden	olden	PROPN
flr-135	340	2	,	,	PUNCT
flr-135	340	3	j.	j.	PROPN
flr-135	340	4	d.	d.	PROPN
flr-135	340	5	,	,	PUNCT
flr-135	340	6	&	&	CCONJ
flr-135	340	7	jackson	jackson	PROPN
flr-135	340	8	,	,	PUNCT
flr-135	340	9	d.	d.	PROPN
flr-135	340	10	a.	a.	PROPN
flr-135	340	11	(	(	PUNCT
flr-135	340	12	2002	2002	NUM
flr-135	340	13	)	)	PUNCT
flr-135	340	14	.	.	PUNCT
flr-135	341	1	illuminating	illuminate	VERB
flr-135	341	2	the	the	DET
flr-135	341	3	''	''	PUNCT
flr-135	341	4	black	black	ADJ
flr-135	341	5	box	box	NOUN
flr-135	341	6	''	''	PUNCT
flr-135	341	7	:	:	PUNCT
flr-135	341	8	a	a	DET
flr-135	341	9	randomization	randomization	NOUN
flr-135	341	10	approach	approach	NOUN
flr-135	341	11	for	for	ADP
flr-135	341	12	understanding	understand	VERB
flr-135	341	13	variable	variable	ADJ
flr-135	341	14	contributions	contribution	NOUN
flr-135	341	15	in	in	ADP
flr-135	341	16	artificial	artificial	ADJ
flr-135	341	17	neural	neural	ADJ
flr-135	341	18	networks	network	NOUN
flr-135	341	19	.	.	PUNCT
flr-135	342	1	ecological	ecological	ADJ
flr-135	342	2	modelling	modelling	NOUN
flr-135	342	3	,	,	PUNCT
flr-135	342	4	154	154	NUM
flr-135	342	5	,	,	PUNCT
flr-135	342	6	135150	135150	NUM
flr-135	342	7	.	.	PUNCT
flr-135	343	1	doi	doi	NOUN
flr-135	343	2	:	:	PUNCT
flr-135	343	3	10.1016	10.1016	NUM
flr-135	343	4	/	/	SYM
flr-135	343	5	s0304	s0304	ADJ
flr-135	343	6	-	-	PUNCT
flr-135	343	7	3800(02)00064	3800(02)00064	NUM
flr-135	343	8	-	-	PUNCT
flr-135	343	9	9	9	NUM
flr-135	343	10	http://dx.doi.org/10.1016/j.compedu.2013.04.001	http://dx.doi.org/10.1016/j.compedu.2013.04.001	NOUN
flr-135	343	11	http://dx.doi.org/10.1016/j.compedu.2013.04.001	http://dx.doi.org/10.1016/j.compedu.2013.04.001	PROPN
flr-135	343	12	http://dx.doi.org/10.1162/neco.1992.4.3.448	http://dx.doi.org/10.1162/neco.1992.4.3.448	NOUN
flr-135	343	13	http://dx.doi.org/10.1109/hicss.1991.184052	http://dx.doi.org/10.1109/hicss.1991.184052	PROPN
flr-135	343	14	http://dx.doi.org/10.14786/flr.v1i1.13	http://dx.doi.org/10.14786/flr.v1i1.13	PROPN
flr-135	344	1	http://dx.doi.org/10.1016/s0304-3800(02)00064-9	http://dx.doi.org/10.1016/s0304-3800(02)00064-9	PROPN
flr-135	344	2	cascallar	cascallar	ADJ
flr-135	344	3	et	et	PROPN
flr-135	344	4	al	al	PROPN
flr-135	344	5	80	80	NUM
flr-135	345	1	|	|	CCONJ
flr-135	345	2	f	f	NOUN
flr-135	345	3	l	l	NOUN
flr-135	345	4	r	r	NOUN
flr-135	345	5	olden	olden	ADJ
flr-135	345	6	,	,	PUNCT
flr-135	345	7	j.	j.	PROPN
flr-135	345	8	d.	d.	PROPN
flr-135	345	9	,	,	PUNCT
flr-135	345	10	joy	joy	PROPN
flr-135	345	11	,	,	PUNCT
flr-135	345	12	m.	m.	PROPN
flr-135	345	13	k.	k.	PROPN
flr-135	345	14	&	&	CCONJ
flr-135	345	15	death	death	PROPN
flr-135	345	16	,	,	PUNCT
flr-135	345	17	r.	r.	PROPN
flr-135	345	18	g.	g.	PROPN
flr-135	345	19	(	(	PUNCT
flr-135	345	20	2004	2004	NUM
flr-135	345	21	)	)	PUNCT
flr-135	345	22	.	.	PUNCT
flr-135	346	1	an	an	DET
flr-135	346	2	accurate	accurate	ADJ
flr-135	346	3	comparison	comparison	NOUN
flr-135	346	4	of	of	ADP
flr-135	346	5	methods	method	NOUN
flr-135	346	6	for	for	ADP
flr-135	346	7	quantifying	quantify	VERB
flr-135	346	8	variable	variable	ADJ
flr-135	346	9	importance	importance	NOUN
flr-135	346	10	in	in	ADP
flr-135	346	11	artificial	artificial	ADJ
flr-135	346	12	neural	neural	ADJ
flr-135	346	13	networks	network	NOUN
flr-135	346	14	using	use	VERB
flr-135	346	15	simulated	simulated	ADJ
flr-135	346	16	data	datum	NOUN
flr-135	346	17	.	.	PUNCT
flr-135	347	1	ecological	ecological	ADJ
flr-135	347	2	modelling	modelling	NOUN
flr-135	347	3	,	,	PUNCT
flr-135	347	4	178	178	NUM
flr-135	347	5	,	,	PUNCT
flr-135	347	6	389	389	NUM
flr-135	347	7	-	-	SYM
flr-135	347	8	397	397	NUM
flr-135	347	9	.	.	PUNCT
flr-135	348	1	doi	doi	NOUN
flr-135	348	2	:	:	PUNCT
flr-135	348	3	10.1016	10.1016	NUM
flr-135	348	4	/	/	SYM
flr-135	348	5	j.ecolmodel.2004.03.013	j.ecolmodel.2004.03.013	PROPN
flr-135	348	6	orre	orre	PROPN
flr-135	348	7	,	,	PUNCT
flr-135	348	8	r.	r.	PROPN
flr-135	348	9	,	,	PUNCT
flr-135	348	10	lansner	lansner	PROPN
flr-135	348	11	,	,	PUNCT
flr-135	348	12	a.	a.	NOUN
flr-135	348	13	,	,	PUNCT
flr-135	348	14	bate	bate	PROPN
flr-135	348	15	,	,	PUNCT
flr-135	348	16	a.	a.	PROPN
flr-135	348	17	,	,	PUNCT
flr-135	348	18	&	&	CCONJ
flr-135	348	19	lindquist	lindquist	PROPN
flr-135	348	20	,	,	PUNCT
flr-135	348	21	m.	m.	NOUN
flr-135	348	22	(	(	PUNCT
flr-135	348	23	2000	2000	NUM
flr-135	348	24	)	)	PUNCT
flr-135	348	25	.	.	PUNCT
flr-135	349	1	bayesian	bayesian	NOUN
flr-135	349	2	neural	neural	ADJ
flr-135	349	3	networks	network	NOUN
flr-135	349	4	with	with	ADP
flr-135	349	5	confidence	confidence	NOUN
flr-135	349	6	estimations	estimation	NOUN
flr-135	349	7	applied	apply	VERB
flr-135	349	8	to	to	ADP
flr-135	349	9	data	datum	NOUN
flr-135	349	10	mining	mining	NOUN
flr-135	349	11	.	.	PUNCT
flr-135	350	1	computational	computational	ADJ
flr-135	350	2	statistics	statistic	NOUN
flr-135	350	3	&	&	CCONJ
flr-135	350	4	data	datum	NOUN
flr-135	350	5	analysis	analysis	NOUN
flr-135	350	6	,	,	PUNCT
flr-135	350	7	34	34	NUM
flr-135	350	8	,	,	PUNCT
flr-135	350	9	473	473	NUM
flr-135	350	10	-	-	SYM
flr-135	350	11	493	493	NUM
flr-135	350	12	.	.	PUNCT
flr-135	351	1	doi	doi	NOUN
flr-135	351	2	:	:	PUNCT
flr-135	351	3	10.1016	10.1016	NUM
flr-135	351	4	/	/	SYM
flr-135	351	5	s0167	s0167	NUM
flr-135	351	6	-	-	PUNCT
flr-135	351	7	9473(99)00114	9473(99)00114	NUM
flr-135	351	8	-	-	PUNCT
flr-135	351	9	0	0	NUM
flr-135	351	10	perkins	perkins	PROPN
flr-135	351	11	,	,	PUNCT
flr-135	351	12	k.	k.	PROPN
flr-135	351	13	,	,	PUNCT
flr-135	351	14	gupta	gupta	PROPN
flr-135	351	15	,	,	PUNCT
flr-135	351	16	l.	l.	PROPN
flr-135	351	17	,	,	PUNCT
flr-135	351	18	&	&	CCONJ
flr-135	351	19	tamanna	tamanna	PROPN
flr-135	351	20	(	(	PUNCT
flr-135	351	21	1995	1995	NUM
flr-135	351	22	)	)	PUNCT
flr-135	351	23	.	.	PUNCT
flr-135	352	1	predict	predict	VERB
flr-135	352	2	item	item	NOUN
flr-135	352	3	difficulty	difficulty	NOUN
flr-135	352	4	in	in	ADP
flr-135	352	5	a	a	DET
flr-135	352	6	reading	reading	NOUN
flr-135	352	7	comprehension	comprehension	NOUN
flr-135	352	8	test	test	NOUN
flr-135	352	9	with	with	ADP
flr-135	352	10	an	an	DET
flr-135	352	11	artificial	artificial	ADJ
flr-135	352	12	neural	neural	ADJ
flr-135	352	13	network	network	NOUN
flr-135	352	14	.	.	PUNCT
flr-135	353	1	language	language	NOUN
flr-135	353	2	testing	testing	NOUN
flr-135	353	3	,	,	PUNCT
flr-135	353	4	12	12	NUM
flr-135	353	5	,	,	PUNCT
flr-135	353	6	34	34	NUM
flr-135	353	7	-	-	SYM
flr-135	353	8	53	53	NUM
flr-135	353	9	.	.	PUNCT
flr-135	354	1	doi	doi	NOUN
flr-135	354	2	:	:	PUNCT
flr-135	354	3	10.1177/026553229501200103	10.1177/026553229501200103	NUM
flr-135	354	4	pinninghoff	pinninghoff	ADJ
flr-135	354	5	junemann	junemann	PROPN
flr-135	354	6	,	,	PUNCT
flr-135	354	7	m.	m.	NOUN
flr-135	354	8	a.	a.	PROPN
flr-135	354	9	,	,	PUNCT
flr-135	354	10	salcedo	salcedo	PROPN
flr-135	354	11	lagos	lagos	PROPN
flr-135	354	12	,	,	PUNCT
flr-135	354	13	p.	p.	NOUN
flr-135	354	14	a.	a.	NOUN
flr-135	354	15	,	,	PUNCT
flr-135	354	16	&	&	CCONJ
flr-135	354	17	contreras	contreras	PROPN
flr-135	354	18	arriagada	arriagada	PROPN
flr-135	354	19	,	,	PUNCT
flr-135	354	20	r.	r.	PROPN
flr-135	354	21	(	(	PUNCT
flr-135	354	22	2007	2007	NUM
flr-135	354	23	)	)	PUNCT
flr-135	354	24	.	.	PUNCT
flr-135	355	1	neural	neural	ADJ
flr-135	355	2	networks	network	NOUN
flr-135	355	3	to	to	PART
flr-135	355	4	predict	predict	VERB
flr-135	355	5	schooling	schooling	NOUN
flr-135	355	6	failure	failure	NOUN
flr-135	355	7	/	/	SYM
flr-135	355	8	success	success	NOUN
flr-135	355	9	.	.	PUNCT
flr-135	356	1	in	in	ADP
flr-135	356	2	j.	j.	PROPN
flr-135	356	3	mira	mira	PROPN
flr-135	356	4	&	&	CCONJ
flr-135	356	5	j.	j.	PROPN
flr-135	356	6	r.	r.	PROPN
flr-135	356	7	alvarez	alvarez	PROPN
flr-135	356	8	(	(	PUNCT
flr-135	356	9	eds	eds	PROPN
flr-135	356	10	.	.	PUNCT
flr-135	356	11	)	)	PUNCT
flr-135	356	12	,	,	PUNCT
flr-135	356	13	nature	nature	NOUN
flr-135	356	14	inspired	inspire	VERB
flr-135	356	15	problemsolving	problemsolve	VERB
flr-135	356	16	methods	method	NOUN
flr-135	356	17	in	in	ADP
flr-135	356	18	knowledge	knowledge	NOUN
flr-135	356	19	engineering	engineering	NOUN
flr-135	356	20	,	,	PUNCT
flr-135	356	21	(	(	PUNCT
flr-135	356	22	part	part	NOUN
flr-135	356	23	ii	ii	PROPN
flr-135	356	24	)	)	PUNCT
flr-135	356	25	,	,	PUNCT
flr-135	356	26	(	(	PUNCT
flr-135	356	27	pp	pp	ADP
flr-135	356	28	.	.	PUNCT
flr-135	357	1	571–579	571–579	NUM
flr-135	357	2	)	)	PUNCT
flr-135	357	3	.	.	PUNCT
flr-135	358	1	berlin	berlin	PROPN
flr-135	358	2	/	/	SYM
flr-135	358	3	heidelberg	heidelberg	PROPN
flr-135	358	4	:	:	PUNCT
flr-135	358	5	springerverlag	springerverlag	NOUN
flr-135	358	6	.	.	PUNCT
flr-135	359	1	doi	doi	NOUN
flr-135	359	2	:	:	PUNCT
flr-135	359	3	10.1007/978	10.1007/978	NUM
flr-135	359	4	-	-	SYM
flr-135	359	5	3	3	NUM
flr-135	359	6	-	-	PUNCT
flr-135	359	7	540	540	NUM
flr-135	359	8	-	-	PUNCT
flr-135	359	9	73055	73055	NUM
flr-135	359	10	-	-	SYM
flr-135	359	11	2_59	2_59	NUM
flr-135	359	12	ramaswami	ramaswami	NOUN
flr-135	359	13	,	,	PUNCT
flr-135	359	14	m.	m.	NOUN
flr-135	359	15	m.	m.	NOUN
flr-135	359	16	,	,	PUNCT
flr-135	359	17	&	&	CCONJ
flr-135	359	18	bhaskaran	bhaskaran	PROPN
flr-135	359	19	,	,	PUNCT
flr-135	359	20	r.	r.	PROPN
flr-135	359	21	r.	r.	PROPN
flr-135	359	22	(	(	PUNCT
flr-135	359	23	2010	2010	NUM
flr-135	359	24	)	)	PUNCT
flr-135	359	25	.	.	PUNCT
flr-135	360	1	a	a	DET
flr-135	360	2	chaid	chaid	NOUN
flr-135	360	3	based	base	VERB
flr-135	360	4	performance	performance	NOUN
flr-135	360	5	prediction	prediction	NOUN
flr-135	360	6	model	model	NOUN
flr-135	360	7	in	in	ADP
flr-135	360	8	educational	educational	ADJ
flr-135	360	9	data	datum	NOUN
flr-135	360	10	mining	mining	NOUN
flr-135	360	11	.	.	PUNCT
flr-135	361	1	international	international	ADJ
flr-135	361	2	journal	journal	PROPN
flr-135	361	3	of	of	ADP
flr-135	361	4	computer	computer	NOUN
flr-135	361	5	science	science	NOUN
flr-135	361	6	issues	issue	NOUN
flr-135	361	7	,	,	PUNCT
flr-135	361	8	7	7	NUM
flr-135	361	9	,	,	PUNCT
flr-135	361	10	10	10	NUM
flr-135	361	11	-	-	SYM
flr-135	361	12	18	18	NUM
flr-135	361	13	.	.	PUNCT
flr-135	362	1	roli	roli	PROPN
flr-135	362	2	,	,	PUNCT
flr-135	362	3	f.	f.	PROPN
flr-135	362	4	,	,	PUNCT
flr-135	362	5	giacinto	giacinto	PROPN
flr-135	362	6	,	,	PUNCT
flr-135	362	7	g.	g.	PROPN
flr-135	362	8	,	,	PUNCT
flr-135	362	9	&	&	CCONJ
flr-135	362	10	vernazza	vernazza	PROPN
flr-135	362	11	,	,	PUNCT
flr-135	362	12	g.	g.	PROPN
flr-135	362	13	(	(	PUNCT
flr-135	362	14	2001	2001	NUM
flr-135	362	15	)	)	PUNCT
flr-135	362	16	.	.	PUNCT
flr-135	363	1	methods	method	NOUN
flr-135	363	2	for	for	ADP
flr-135	363	3	designing	design	VERB
flr-135	363	4	multiple	multiple	ADJ
flr-135	363	5	classifier	classifier	NOUN
flr-135	363	6	systems	system	NOUN
flr-135	363	7	.	.	PUNCT
flr-135	364	1	in	in	ADP
flr-135	364	2	j.	j.	PROPN
flr-135	364	3	kittler	kittler	PROPN
flr-135	364	4	&	&	CCONJ
flr-135	364	5	f.	f.	PROPN
flr-135	364	6	roli	roli	PROPN
flr-135	364	7	(	(	PUNCT
flr-135	364	8	eds	ed	NOUN
flr-135	364	9	.	.	PUNCT
flr-135	364	10	)	)	PUNCT
flr-135	364	11	,	,	PUNCT
flr-135	364	12	multiple	multiple	ADJ
flr-135	364	13	classifier	classifier	NOUN
flr-135	364	14	systems	system	NOUN
flr-135	364	15	,	,	PUNCT
flr-135	364	16	(	(	PUNCT
flr-135	364	17	pp	pp	ADV
flr-135	364	18	.	.	PUNCT
flr-135	364	19	78	78	NUM
flr-135	364	20	-	-	SYM
flr-135	364	21	87	87	NUM
flr-135	364	22	)	)	PUNCT
flr-135	364	23	.	.	PUNCT
flr-135	365	1	berlin	berlin	PROPN
flr-135	365	2	/	/	SYM
flr-135	365	3	heidelberg	heidelberg	PROPN
flr-135	365	4	:	:	PUNCT
flr-135	365	5	springer	springer	NOUN
flr-135	365	6	-	-	PUNCT
flr-135	365	7	verlag	verlag	PROPN
flr-135	365	8	.	.	PUNCT
flr-135	366	1	doi	doi	PROPN
flr-135	366	2	:	:	PUNCT
flr-135	366	3	10.1007/3	10.1007/3	NUM
flr-135	366	4	-	-	PUNCT
flr-135	366	5	540	540	NUM
flr-135	366	6	-	-	PUNCT
flr-135	366	7	48219	48219	NUM
flr-135	366	8	-	-	PUNCT
flr-135	366	9	9_8	9_8	NUM
flr-135	366	10	ripley	ripley	NOUN
flr-135	366	11	,	,	PUNCT
flr-135	366	12	b.	b.	PROPN
flr-135	366	13	d.	d.	PROPN
flr-135	366	14	(	(	PUNCT
flr-135	366	15	1996	1996	NUM
flr-135	366	16	)	)	PUNCT
flr-135	366	17	.	.	PUNCT
flr-135	367	1	pattern	pattern	NOUN
flr-135	367	2	recognition	recognition	NOUN
flr-135	367	3	and	and	CCONJ
flr-135	367	4	neural	neural	ADJ
flr-135	367	5	networks	network	NOUN
flr-135	367	6	.	.	PUNCT
flr-135	368	1	cambridge	cambridge	PROPN
flr-135	368	2	:	:	PUNCT
flr-135	368	3	cambridge	cambridge	PROPN
flr-135	368	4	university	university	PROPN
flr-135	368	5	press	press	NOUN
flr-135	368	6	.	.	PUNCT
flr-135	369	1	doi	doi	NOUN
flr-135	369	2	:	:	PUNCT
flr-135	369	3	10.1017	10.1017	NUM
flr-135	369	4	/	/	SYM
flr-135	369	5	cbo9780511812651	cbo9780511812651	NOUN
flr-135	369	6	rivals	rival	NOUN
flr-135	369	7	,	,	PUNCT
flr-135	369	8	i.	i.	PROPN
flr-135	369	9	,	,	PUNCT
flr-135	369	10	&	&	CCONJ
flr-135	369	11	personnaz	personnaz	PROPN
flr-135	369	12	,	,	PUNCT
flr-135	369	13	l.	l.	PROPN
flr-135	369	14	(	(	PUNCT
flr-135	369	15	2000	2000	NUM
flr-135	369	16	)	)	PUNCT
flr-135	369	17	.	.	PUNCT
flr-135	370	1	construction	construction	NOUN
flr-135	370	2	of	of	ADP
flr-135	370	3	confidence	confidence	NOUN
flr-135	370	4	intervals	interval	NOUN
flr-135	370	5	for	for	ADP
flr-135	370	6	neural	neural	ADJ
flr-135	370	7	networks	network	NOUN
flr-135	370	8	based	base	VERB
flr-135	370	9	on	on	ADP
flr-135	370	10	least	least	ADJ
flr-135	370	11	squares	square	NOUN
flr-135	370	12	estimations	estimation	NOUN
flr-135	370	13	.	.	PUNCT
flr-135	371	1	neural	neural	ADJ
flr-135	371	2	networks	network	NOUN
flr-135	371	3	,	,	PUNCT
flr-135	371	4	13	13	NUM
flr-135	371	5	,	,	PUNCT
flr-135	371	6	463	463	NUM
flr-135	371	7	-	-	SYM
flr-135	371	8	484	484	NUM
flr-135	371	9	.	.	PUNCT
flr-135	372	1	doi	doi	NOUN
flr-135	372	2	:	:	PUNCT
flr-135	372	3	10.1016	10.1016	NUM
flr-135	372	4	/	/	SYM
flr-135	372	5	s0893	s0893	NOUN
flr-135	372	6	-	-	PUNCT
flr-135	372	7	6080(99)00080	6080(99)00080	NUM
flr-135	372	8	-	-	PUNCT
flr-135	372	9	5	5	NUM
flr-135	372	10	rokach	rokach	NOUN
flr-135	372	11	,	,	PUNCT
flr-135	372	12	l.	l.	PROPN
flr-135	372	13	(	(	PUNCT
flr-135	372	14	2010	2010	NUM
flr-135	372	15	)	)	PUNCT
flr-135	372	16	.	.	PUNCT
flr-135	373	1	ensemble	ensemble	ADJ
flr-135	373	2	-	-	PUNCT
flr-135	373	3	based	base	VERB
flr-135	373	4	classifiers	classifier	NOUN
flr-135	373	5	.	.	PUNCT
flr-135	374	1	artificial	artificial	ADJ
flr-135	374	2	intelligence	intelligence	NOUN
flr-135	374	3	review	review	NOUN
flr-135	374	4	,	,	PUNCT
flr-135	374	5	33	33	NUM
flr-135	374	6	,	,	PUNCT
flr-135	374	7	1	1	NUM
flr-135	374	8	-	-	SYM
flr-135	374	9	39	39	NUM
flr-135	374	10	.	.	PUNCT
flr-135	375	1	doi	doi	NOUN
flr-135	375	2	:	:	PUNCT
flr-135	375	3	10.1007	10.1007	NUM
flr-135	375	4	/	/	SYM
flr-135	375	5	s10462	s10462	NOUN
flr-135	375	6	-	-	PUNCT
flr-135	375	7	009	009	NUM
flr-135	375	8	-	-	PUNCT
flr-135	375	9	9124	9124	NUM
flr-135	375	10	-	-	SYM
flr-135	375	11	7	7	NUM
flr-135	375	12	sahu	sahu	PROPN
flr-135	375	13	,	,	PUNCT
flr-135	375	14	a.	a.	NOUN
flr-135	375	15	,	,	PUNCT
flr-135	375	16	runger	runger	NOUN
flr-135	375	17	,	,	PUNCT
flr-135	375	18	g.	g.	PROPN
flr-135	375	19	,	,	PUNCT
flr-135	375	20	apley	apley	PROPN
flr-135	375	21	,	,	PUNCT
flr-135	375	22	d.	d.	PROPN
flr-135	375	23	(	(	PUNCT
flr-135	375	24	2011	2011	NUM
flr-135	375	25	)	)	PUNCT
flr-135	375	26	.	.	PUNCT
flr-135	376	1	image	image	NOUN
flr-135	376	2	denoising	denoise	VERB
flr-135	376	3	with	with	ADP
flr-135	376	4	a	a	DET
flr-135	376	5	multi	multi	ADJ
flr-135	376	6	-	-	ADJ
flr-135	376	7	phase	phase	ADJ
flr-135	376	8	kernel	kernel	NOUN
flr-135	376	9	principal	principal	NOUN
flr-135	376	10	component	component	NOUN
flr-135	376	11	approach	approach	NOUN
flr-135	376	12	and	and	CCONJ
flr-135	376	13	an	an	DET
flr-135	376	14	ensemble	ensemble	ADJ
flr-135	376	15	version	version	NOUN
flr-135	376	16	.	.	PUNCT
flr-135	377	1	ieee	ieee	NOUN
flr-135	377	2	applied	apply	VERB
flr-135	377	3	imagery	imagery	NOUN
flr-135	377	4	pattern	pattern	NOUN
flr-135	377	5	recognition	recognition	NOUN
flr-135	377	6	workshop	workshop	NOUN
flr-135	377	7	,	,	PUNCT
flr-135	377	8	1	1	NUM
flr-135	377	9	-	-	SYM
flr-135	377	10	7	7	NUM
flr-135	377	11	.	.	PUNCT
flr-135	377	12	schermelleh	schermelleh	NOUN
flr-135	377	13	-	-	PUNCT
flr-135	377	14	engel	engel	PROPN
flr-135	377	15	,	,	PUNCT
flr-135	377	16	k.	k.	PROPN
flr-135	377	17	,	,	PUNCT
flr-135	377	18	kerwer	kerwer	PROPN
flr-135	377	19	,	,	PUNCT
flr-135	377	20	m.	m.	NOUN
flr-135	377	21	,	,	PUNCT
flr-135	377	22	&	&	CCONJ
flr-135	377	23	klein	klein	PROPN
flr-135	377	24	,	,	PUNCT
flr-135	377	25	a.	a.	PROPN
flr-135	377	26	g.	g.	PROPN
flr-135	377	27	(	(	PUNCT
flr-135	377	28	2014	2014	NUM
flr-135	377	29	)	)	PUNCT
flr-135	377	30	.	.	PUNCT
flr-135	378	1	evaluation	evaluation	NOUN
flr-135	378	2	of	of	ADP
flr-135	378	3	model	model	NOUN
flr-135	378	4	fit	fit	ADJ
flr-135	378	5	in	in	ADP
flr-135	378	6	nonlinear	nonlinear	ADJ
flr-135	378	7	multilevel	multilevel	ADJ
flr-135	378	8	structural	structural	ADJ
flr-135	378	9	equation	equation	NOUN
flr-135	378	10	modelling	modelling	NOUN
flr-135	378	11	.	.	PUNCT
flr-135	379	1	frontiers	frontier	NOUN
flr-135	379	2	in	in	ADP
flr-135	379	3	psychology	psychology	NOUN
flr-135	379	4	,	,	PUNCT
flr-135	379	5	5	5	NUM
flr-135	379	6	,	,	PUNCT
flr-135	379	7	article	article	NOUN
flr-135	379	8	181	181	NUM
flr-135	379	9	,	,	PUNCT
flr-135	379	10	1	1	NUM
flr-135	379	11	-	-	SYM
flr-135	379	12	11	11	NUM
flr-135	379	13	.	.	PUNCT
flr-135	380	1	doi	doi	NOUN
flr-135	380	2	:	:	PUNCT
flr-135	380	3	10.3389	10.3389	NUM
flr-135	380	4	/	/	SYM
flr-135	380	5	fpsyg.2014.00181	fpsyg.2014.00181	PROPN
flr-135	380	6	.	.	PUNCT
flr-135	381	1	suppes	suppe	NOUN
flr-135	381	2	,	,	PUNCT
flr-135	381	3	p.	p.	NOUN
flr-135	381	4	(	(	PUNCT
flr-135	381	5	1962	1962	NUM
flr-135	381	6	)	)	PUNCT
flr-135	381	7	.	.	PUNCT
flr-135	382	1	models	model	NOUN
flr-135	382	2	of	of	ADP
flr-135	382	3	data	datum	NOUN
flr-135	382	4	.	.	PUNCT
flr-135	383	1	in	in	ADP
flr-135	383	2	e.	e.	PROPN
flr-135	383	3	nagel	nagel	PROPN
flr-135	383	4	,	,	PUNCT
flr-135	383	5	p.	p.	NOUN
flr-135	383	6	suppes	suppe	NOUN
flr-135	383	7	&	&	CCONJ
flr-135	383	8	a.	a.	PROPN
flr-135	383	9	tarski	tarski	PROPN
flr-135	383	10	(	(	PUNCT
flr-135	383	11	eds	ed	NOUN
flr-135	383	12	.	.	PUNCT
flr-135	383	13	)	)	PUNCT
flr-135	383	14	,	,	PUNCT
flr-135	383	15	logic	logic	NOUN
flr-135	383	16	,	,	PUNCT
flr-135	383	17	methodology	methodology	NOUN
flr-135	383	18	and	and	CCONJ
flr-135	383	19	philosophy	philosophy	NOUN
flr-135	383	20	of	of	ADP
flr-135	383	21	science	science	NOUN
flr-135	383	22	:	:	PUNCT
flr-135	383	23	proceedings	proceeding	NOUN
flr-135	383	24	of	of	ADP
flr-135	383	25	the	the	DET
flr-135	383	26	1960	1960	NUM
flr-135	383	27	international	international	ADJ
flr-135	383	28	congress	congress	PROPN
flr-135	383	29	.	.	PUNCT
flr-135	384	1	stanford	stanford	PROPN
flr-135	384	2	:	:	PUNCT
flr-135	384	3	stanford	stanford	PROPN
flr-135	384	4	university	university	PROPN
flr-135	384	5	press	press	NOUN
flr-135	384	6	,	,	PUNCT
flr-135	384	7	252	252	NUM
flr-135	384	8	-	-	SYM
flr-135	384	9	261	261	NUM
flr-135	384	10	.	.	PUNCT
flr-135	385	1	thrush	thrush	NOUN
flr-135	385	2	,	,	PUNCT
flr-135	385	3	s.	s.	PROPN
flr-135	385	4	f.	f.	PROPN
flr-135	385	5	,	,	PUNCT
flr-135	385	6	coco	coco	PROPN
flr-135	385	7	,	,	PUNCT
flr-135	385	8	g.	g.	PROPN
flr-135	385	9	,	,	PUNCT
flr-135	385	10	&	&	CCONJ
flr-135	385	11	hewitt	hewitt	PROPN
flr-135	385	12	,	,	PUNCT
flr-135	385	13	j.	j.	PROPN
flr-135	385	14	e.	e.	PROPN
flr-135	385	15	(	(	PUNCT
flr-135	385	16	2008	2008	NUM
flr-135	385	17	)	)	PUNCT
flr-135	385	18	.	.	PUNCT
flr-135	386	1	complex	complex	ADJ
flr-135	386	2	positive	positive	ADJ
flr-135	386	3	connections	connection	NOUN
flr-135	386	4	between	between	ADP
flr-135	386	5	functional	functional	ADJ
flr-135	386	6	groups	group	NOUN
flr-135	386	7	are	be	AUX
flr-135	386	8	revealed	reveal	VERB
flr-135	386	9	by	by	ADP
flr-135	386	10	neural	neural	ADJ
flr-135	386	11	network	network	NOUN
flr-135	386	12	analysis	analysis	NOUN
flr-135	386	13	of	of	ADP
flr-135	386	14	ecological	ecological	ADJ
flr-135	386	15	time	time	NOUN
flr-135	386	16	series	series	PROPN
flr-135	386	17	.	.	PUNCT
flr-135	387	1	american	american	PROPN
flr-135	387	2	naturalist	naturalist	PROPN
flr-135	387	3	171	171	NUM
flr-135	387	4	,	,	PUNCT
flr-135	387	5	669	669	NUM
flr-135	387	6	-	-	SYM
flr-135	387	7	677	677	NUM
flr-135	387	8	.	.	PUNCT
flr-135	388	1	doi	doi	NOUN
flr-135	388	2	:	:	PUNCT
flr-135	388	3	10.1086/587069	10.1086/587069	NUM
flr-135	388	4	http://dx.doi.org/10.1016/j.ecolmodel.2004.03.013	http://dx.doi.org/10.1016/j.ecolmodel.2004.03.013	PROPN
flr-135	388	5	http://dx.doi.org/10.1016/s0167-9473(99)00114-0	http://dx.doi.org/10.1016/s0167-9473(99)00114-0	PROPN
flr-135	388	6	http://dx.doi.org/10.1016/s0167-9473(99)00114-0	http://dx.doi.org/10.1016/s0167-9473(99)00114-0	PROPN
flr-135	388	7	http://dx.doi.org/10.1177/026553229501200103	http://dx.doi.org/10.1177/026553229501200103	NOUN
flr-135	388	8	http://dx.doi.org/10.1007/978-3-540-73055-2_59	http://dx.doi.org/10.1007/978-3-540-73055-2_59	PROPN
flr-135	388	9	http://dx.doi.org/10.1007/3-540-48219-9_8	http://dx.doi.org/10.1007/3-540-48219-9_8	NOUN
flr-135	388	10	http://dx.doi.org/10.1007/3-540-48219-9_8	http://dx.doi.org/10.1007/3-540-48219-9_8	X
flr-135	388	11	http://dx.doi.org/10.1017/cbo9780511812651	http://dx.doi.org/10.1017/cbo9780511812651	PROPN
flr-135	388	12	http://dx.doi.org/10.1016/s0893-6080(99)00080-5	http://dx.doi.org/10.1016/s0893-6080(99)00080-5	NUM
flr-135	388	13	http://dx.doi.org/10.1007/s10462-009-9124-7	http://dx.doi.org/10.1007/s10462-009-9124-7	NOUN
flr-135	388	14	http://dx.doi.org/10.1007/s10462-009-9124-7	http://dx.doi.org/10.1007/s10462-009-9124-7	NOUN
flr-135	388	15	http://dx.doi.org/10.1086/587069	http://dx.doi.org/10.1086/587069	NOUN
flr-135	388	16	cascallar	cascallar	ADJ
flr-135	388	17	et	et	PROPN
flr-135	388	18	al	al	PROPN
flr-135	388	19	81	81	NUM
flr-135	389	1	|	|	ADV
flr-135	389	2	f	f	NOUN
flr-135	389	3	l	l	NOUN
flr-135	389	4	r	r	NOUN
flr-135	389	5	tzeng	tzeng	PROPN
flr-135	389	6	,	,	PUNCT
flr-135	389	7	f.	f.	PROPN
flr-135	389	8	y.	y.	PROPN
flr-135	389	9	,	,	PUNCT
flr-135	389	10	&	&	CCONJ
flr-135	389	11	ma	ma	PROPN
flr-135	389	12	,	,	PUNCT
flr-135	389	13	k.	k.	PROPN
flr-135	389	14	l.	l.	PROPN
flr-135	389	15	(	(	PUNCT
flr-135	389	16	2005	2005	NUM
flr-135	389	17	)	)	PUNCT
flr-135	389	18	.	.	PUNCT
flr-135	390	1	intelligent	intelligent	ADJ
flr-135	390	2	feature	feature	NOUN
flr-135	390	3	extraction	extraction	NOUN
flr-135	390	4	and	and	CCONJ
flr-135	390	5	tracking	tracking	NOUN
flr-135	390	6	for	for	ADP
flr-135	390	7	visualizing	visualize	VERB
flr-135	390	8	large	large	ADJ
flr-135	390	9	-	-	PUNCT
flr-135	390	10	scale	scale	NOUN
flr-135	390	11	4d	4d	NUM
flr-135	390	12	flow	flow	NOUN
flr-135	390	13	simulations	simulation	NOUN
flr-135	390	14	.	.	PUNCT
flr-135	391	1	in	in	ADP
flr-135	391	2	dvd	dvd	NOUN
flr-135	391	3	proceedings	proceeding	NOUN
flr-135	391	4	of	of	ADP
flr-135	391	5	the	the	DET
flr-135	391	6	international	international	ADJ
flr-135	391	7	conference	conference	NOUN
flr-135	391	8	for	for	ADP
flr-135	391	9	high	high	ADJ
flr-135	391	10	performance	performance	NOUN
flr-135	391	11	computing	computing	NOUN
flr-135	391	12	,	,	PUNCT
flr-135	391	13	networking	networking	NOUN
flr-135	391	14	,	,	PUNCT
flr-135	391	15	storage	storage	NOUN
flr-135	391	16	and	and	CCONJ
flr-135	391	17	analysis	analysis	NOUN
flr-135	391	18	(	(	PUNCT
flr-135	391	19	sc	sc	PROPN
flr-135	391	20	'	'	NUM
flr-135	391	21	05	05	NUM
flr-135	391	22	)	)	PUNCT
flr-135	391	23	.	.	PUNCT
flr-135	392	1	november	november	PROPN
flr-135	392	2	,	,	PUNCT
flr-135	392	3	2005	2005	NUM
flr-135	392	4	.	.	PUNCT
flr-135	393	1	weiss	weiss	PROPN
flr-135	393	2	,	,	PUNCT
flr-135	393	3	s.	s.	PROPN
flr-135	393	4	m.	m.	PROPN
flr-135	393	5	,	,	PUNCT
flr-135	393	6	&	&	CCONJ
flr-135	393	7	kulikowski	kulikowski	PROPN
flr-135	393	8	,	,	PUNCT
flr-135	393	9	c.	c.	PROPN
flr-135	393	10	a.	a.	PROPN
flr-135	393	11	(	(	PUNCT
flr-135	393	12	1991	1991	NUM
flr-135	393	13	)	)	PUNCT
flr-135	393	14	.	.	PUNCT
flr-135	394	1	computer	computer	NOUN
flr-135	394	2	systems	system	NOUN
flr-135	394	3	that	that	PRON
flr-135	394	4	learn	learn	VERB
flr-135	394	5	.	.	PUNCT
flr-135	395	1	san	san	PROPN
flr-135	395	2	mateo	mateo	PROPN
flr-135	395	3	,	,	PUNCT
flr-135	395	4	ca	ca	PROPN
flr-135	395	5	:	:	PUNCT
flr-135	395	6	morgan	morgan	PROPN
flr-135	395	7	kaufmann	kaufmann	PROPN
flr-135	395	8	publishers	publishers	PROPN
flr-135	395	9	.	.	PUNCT
flr-135	396	1	west	west	PROPN
flr-135	396	2	,	,	PUNCT
flr-135	396	3	p.	p.	NOUN
flr-135	396	4	m.	m.	NOUN
flr-135	396	5	,	,	PUNCT
flr-135	396	6	brockett	brockett	PROPN
flr-135	396	7	,	,	PUNCT
flr-135	396	8	p.	p.	PROPN
flr-135	396	9	l.	l.	PROPN
flr-135	396	10	,	,	PUNCT
flr-135	396	11	&	&	CCONJ
flr-135	396	12	golden	golden	PROPN
flr-135	396	13	,	,	PUNCT
flr-135	396	14	l.	l.	PROPN
flr-135	396	15	l.	l.	PROPN
flr-135	396	16	(	(	PUNCT
flr-135	396	17	1997	1997	NUM
flr-135	396	18	)	)	PUNCT
flr-135	396	19	.	.	PUNCT
flr-135	397	1	a	a	DET
flr-135	397	2	comparative	comparative	ADJ
flr-135	397	3	analysis	analysis	NOUN
flr-135	397	4	of	of	ADP
flr-135	397	5	neural	neural	ADJ
flr-135	397	6	networks	network	NOUN
flr-135	397	7	and	and	CCONJ
flr-135	397	8	statistical	statistical	ADJ
flr-135	397	9	methods	method	NOUN
flr-135	397	10	for	for	ADP
flr-135	397	11	predicting	predict	VERB
flr-135	397	12	consumer	consumer	NOUN
flr-135	397	13	choice	choice	NOUN
flr-135	397	14	.	.	PUNCT
flr-135	398	1	marketing	marketing	NOUN
flr-135	398	2	science	science	NOUN
flr-135	398	3	,	,	PUNCT
flr-135	398	4	16	16	NUM
flr-135	398	5	,	,	PUNCT
flr-135	398	6	370	370	NUM
flr-135	398	7	-	-	SYM
flr-135	398	8	391	391	NUM
flr-135	398	9	.	.	PUNCT
flr-135	399	1	doi	doi	NOUN
flr-135	399	2	:	:	PUNCT
flr-135	399	3	10.1287	10.1287	NUM
flr-135	399	4	/	/	SYM
flr-135	399	5	mksc.16.4.370	mksc.16.4.370	PROPN
flr-135	399	6	weston	weston	PROPN
flr-135	399	7	,	,	PUNCT
flr-135	399	8	r.	r.	PROPN
flr-135	399	9	,	,	PUNCT
flr-135	399	10	&	&	CCONJ
flr-135	399	11	gore	gore	PROPN
flr-135	399	12	,	,	PUNCT
flr-135	399	13	p.	p.	NOUN
flr-135	399	14	a.	a.	NOUN
flr-135	400	1	(	(	PUNCT
flr-135	400	2	2006	2006	NUM
flr-135	400	3	)	)	PUNCT
flr-135	400	4	.	.	PUNCT
flr-135	401	1	a	a	DET
flr-135	401	2	brief	brief	ADJ
flr-135	401	3	guide	guide	NOUN
flr-135	401	4	to	to	ADP
flr-135	401	5	structural	structural	ADJ
flr-135	401	6	equation	equation	NOUN
flr-135	401	7	modeling	modeling	NOUN
flr-135	401	8	.	.	PUNCT
flr-135	402	1	the	the	DET
flr-135	402	2	counseling	counseling	NOUN
flr-135	402	3	psychologist	psychologist	NOUN
flr-135	402	4	,	,	PUNCT
flr-135	402	5	34	34	NUM
flr-135	402	6	,	,	PUNCT
flr-135	402	7	719	719	NUM
flr-135	402	8	-	-	SYM
flr-135	402	9	751	751	NUM
flr-135	402	10	.	.	PUNCT
flr-135	403	1	doi	doi	NOUN
flr-135	403	2	:	:	PUNCT
flr-135	403	3	10.1177/0011000006286345	10.1177/0011000006286345	NUM
flr-135	403	4	white	white	ADJ
flr-135	403	5	,	,	PUNCT
flr-135	403	6	h.	h.	PROPN
flr-135	403	7	,	,	PUNCT
flr-135	403	8	&	&	CCONJ
flr-135	403	9	racine	racine	PROPN
flr-135	403	10	,	,	PUNCT
flr-135	403	11	j.	j.	PROPN
flr-135	403	12	(	(	PUNCT
flr-135	403	13	2001	2001	NUM
flr-135	403	14	)	)	PUNCT
flr-135	403	15	.	.	PUNCT
flr-135	404	1	statistical	statistical	ADJ
flr-135	404	2	inference	inference	NOUN
flr-135	404	3	,	,	PUNCT
flr-135	404	4	the	the	DET
flr-135	404	5	bootstrap	bootstrap	NOUN
flr-135	404	6	,	,	PUNCT
flr-135	404	7	and	and	CCONJ
flr-135	404	8	neural	neural	ADJ
flr-135	404	9	network	network	NOUN
flr-135	404	10	modelling	modelling	NOUN
flr-135	404	11	with	with	ADP
flr-135	404	12	application	application	NOUN
flr-135	404	13	to	to	ADP
flr-135	404	14	foreign	foreign	ADJ
flr-135	404	15	exchange	exchange	NOUN
flr-135	404	16	rates	rate	NOUN
flr-135	404	17	.	.	PUNCT
flr-135	405	1	ieee	ieee	NOUN
flr-135	405	2	transactions	transaction	NOUN
flr-135	405	3	on	on	ADP
flr-135	405	4	neural	neural	ADJ
flr-135	405	5	networks	network	NOUN
flr-135	405	6	,	,	PUNCT
flr-135	405	7	12	12	NUM
flr-135	405	8	,	,	PUNCT
flr-135	405	9	657	657	NUM
flr-135	405	10	-	-	SYM
flr-135	405	11	673	673	NUM
flr-135	405	12	.	.	PUNCT
flr-135	406	1	doi	doi	NOUN
flr-135	406	2	:	:	PUNCT
flr-135	406	3	10.1109/72.935080	10.1109/72.935080	PROPN
flr-135	406	4	wilson	wilson	PROPN
flr-135	406	5	,	,	PUNCT
flr-135	406	6	r.	r.	PROPN
flr-135	406	7	l.	l.	PROPN
flr-135	406	8	,	,	PUNCT
flr-135	406	9	&	&	CCONJ
flr-135	406	10	hardgrave	hardgrave	PROPN
flr-135	406	11	,	,	PUNCT
flr-135	406	12	b.	b.	PROPN
flr-135	406	13	c.	c.	PROPN
flr-135	406	14	(	(	PUNCT
flr-135	406	15	1995	1995	NUM
flr-135	406	16	)	)	PUNCT
flr-135	406	17	.	.	PUNCT
flr-135	407	1	predicting	predict	VERB
flr-135	407	2	graduate	graduate	NOUN
flr-135	407	3	student	student	NOUN
flr-135	407	4	success	success	NOUN
flr-135	407	5	in	in	ADP
flr-135	407	6	an	an	DET
flr-135	407	7	mba	mba	NOUN
flr-135	407	8	program	program	NOUN
flr-135	407	9	:	:	PUNCT
flr-135	407	10	regression	regression	NOUN
flr-135	407	11	versus	versus	ADP
flr-135	407	12	classification	classification	NOUN
flr-135	407	13	.	.	PUNCT
flr-135	408	1	educational	educational	ADJ
flr-135	408	2	and	and	CCONJ
flr-135	408	3	psychological	psychological	ADJ
flr-135	408	4	measurement	measurement	NOUN
flr-135	408	5	,	,	PUNCT
flr-135	408	6	55	55	NUM
flr-135	408	7	,	,	PUNCT
flr-135	408	8	186	186	NUM
flr-135	408	9	-	-	SYM
flr-135	408	10	195	195	NUM
flr-135	408	11	.	.	PUNCT
flr-135	408	12	doi	doi	NOUN
flr-135	408	13	:	:	PUNCT
flr-135	408	14	10.1177/0013164495055002003	10.1177/0013164495055002003	NUM
flr-135	408	15	yeh	yeh	PROPN
flr-135	408	16	,	,	PUNCT
flr-135	408	17	i.	i.	PROPN
flr-135	408	18	c.	c.	PROPN
flr-135	408	19	,	,	PUNCT
flr-135	408	20	&	&	CCONJ
flr-135	408	21	cheng	cheng	PROPN
flr-135	408	22	,	,	PUNCT
flr-135	408	23	w.	w.	PROPN
flr-135	408	24	l.	l.	PROPN
flr-135	408	25	(	(	PUNCT
flr-135	408	26	2010	2010	NUM
flr-135	408	27	)	)	PUNCT
flr-135	408	28	.	.	PUNCT
flr-135	409	1	first	first	ADJ
flr-135	409	2	and	and	CCONJ
flr-135	409	3	second	second	ADJ
flr-135	409	4	order	order	NOUN
flr-135	409	5	sensitivity	sensitivity	NOUN
flr-135	409	6	analysis	analysis	NOUN
flr-135	409	7	of	of	ADP
flr-135	409	8	mlp	mlp	PROPN
flr-135	409	9	.	.	PUNCT
flr-135	410	1	neurocomputing	neurocomputing	PROPN
flr-135	410	2	,	,	PUNCT
flr-135	410	3	73	73	NUM
flr-135	410	4	,	,	PUNCT
flr-135	410	5	2225	2225	NUM
flr-135	410	6	-	-	SYM
flr-135	410	7	2233	2233	NUM
flr-135	410	8	.	.	PUNCT
flr-135	411	1	doi	doi	NOUN
flr-135	411	2	:	:	PUNCT
flr-135	411	3	10.1016	10.1016	NUM
flr-135	411	4	/	/	SYM
flr-135	411	5	j.neucom.2010.01.011	j.neucom.2010.01.011	PROPN
flr-135	411	6	zambrano	zambrano	PROPN
flr-135	411	7	matamala	matamala	PROPN
flr-135	411	8	,	,	PUNCT
flr-135	411	9	c.	c.	PROPN
flr-135	411	10	,	,	PUNCT
flr-135	411	11	rojas	rojas	PROPN
flr-135	411	12	díaz	díaz	PROPN
flr-135	411	13	,	,	PUNCT
flr-135	411	14	d.	d.	PROPN
flr-135	411	15	,	,	PUNCT
flr-135	411	16	carvajal	carvajal	PROPN
flr-135	411	17	cuello	cuello	PROPN
flr-135	411	18	,	,	PUNCT
flr-135	411	19	k.	k.	PROPN
flr-135	411	20	,	,	PUNCT
flr-135	411	21	&	&	CCONJ
flr-135	411	22	acu	acu	PROPN
flr-135	411	23	-	-	PUNCT
flr-135	411	24	a	a	DET
flr-135	411	25	leiva	leiva	NOUN
flr-135	411	26	,	,	PUNCT
flr-135	411	27	g.	g.	PROPN
flr-135	411	28	(	(	PUNCT
flr-135	411	29	2011	2011	NUM
flr-135	411	30	)	)	PUNCT
flr-135	411	31	.	.	PUNCT
flr-135	412	1	análisis	análisis	PROPN
flr-135	412	2	de	de	PROPN
flr-135	412	3	rendimiento	rendimiento	PROPN
flr-135	412	4	académico	académico	PROPN
flr-135	412	5	estudiantil	estudiantil	PROPN
flr-135	412	6	usando	usando	PROPN
flr-135	412	7	data	data	PROPN
flr-135	412	8	warehouse	warehouse	PROPN
flr-135	412	9	y	y	PROPN
flr-135	412	10	redes	redes	PROPN
flr-135	412	11	neuronales	neuronales	PROPN
flr-135	412	12	.	.	PUNCT
flr-135	413	1	[	[	X
flr-135	413	2	analysis	analysis	NOUN
flr-135	413	3	of	of	ADP
flr-135	413	4	students	student	NOUN
flr-135	413	5	'	'	PART
flr-135	413	6	academic	academic	ADJ
flr-135	413	7	performance	performance	NOUN
flr-135	413	8	using	use	VERB
flr-135	413	9	data	datum	NOUN
flr-135	413	10	warehouse	warehouse	NOUN
flr-135	413	11	and	and	CCONJ
flr-135	413	12	neural	neural	ADJ
flr-135	413	13	networks	network	NOUN
flr-135	413	14	]	]	PUNCT
flr-135	413	15	ingeniare	ingeniare	PROPN
flr-135	413	16	.	.	PUNCT
flr-135	414	1	revista	revista	PROPN
flr-135	414	2	chilena	chilena	PROPN
flr-135	414	3	de	de	PROPN
flr-135	414	4	ingeniería	ingeniería	PROPN
flr-135	414	5	,	,	PUNCT
flr-135	414	6	19	19	NUM
flr-135	414	7	,	,	PUNCT
flr-135	414	8	369	369	NUM
flr-135	414	9	-	-	SYM
flr-135	414	10	381	381	NUM
flr-135	414	11	.	.	PUNCT
flr-135	415	1	doi	doi	NOUN
flr-135	415	2	:	:	PUNCT
flr-135	415	3	10.4067	10.4067	NUM
flr-135	415	4	/	/	SYM
flr-135	415	5	s0718	s0718	NOUN
flr-135	415	6	-	-	PUNCT
flr-135	415	7	33052011000300007	33052011000300007	NUM
flr-135	415	8	zapranis	zapranis	NOUN
flr-135	415	9	,	,	PUNCT
flr-135	415	10	a.	a.	NOUN
flr-135	415	11	,	,	PUNCT
flr-135	415	12	&	&	CCONJ
flr-135	415	13	livanis	livanis	PROPN
flr-135	415	14	,	,	PUNCT
flr-135	415	15	e.	e.	PROPN
flr-135	415	16	(	(	PUNCT
flr-135	415	17	2005	2005	NUM
flr-135	415	18	)	)	PUNCT
flr-135	415	19	.	.	PUNCT
flr-135	416	1	prediction	prediction	NOUN
flr-135	416	2	intervals	interval	NOUN
flr-135	416	3	for	for	ADP
flr-135	416	4	neural	neural	ADJ
flr-135	416	5	network	network	NOUN
flr-135	416	6	models	model	NOUN
flr-135	416	7	.	.	PUNCT
flr-135	417	1	proceedings	proceeding	NOUN
flr-135	417	2	of	of	ADP
flr-135	417	3	the	the	DET
flr-135	417	4	9th	9th	ADJ
flr-135	417	5	wseas	wseas	NOUN
flr-135	417	6	international	international	ADJ
flr-135	417	7	conference	conference	NOUN
flr-135	417	8	on	on	ADP
flr-135	417	9	computers	computer	NOUN
flr-135	417	10	(	(	PUNCT
flr-135	417	11	iccomp'05	iccomp'05	PROPN
flr-135	417	12	)	)	PUNCT
flr-135	417	13	.	.	PUNCT
flr-135	418	1	world	world	NOUN
flr-135	418	2	scientific	scientific	ADJ
flr-135	418	3	and	and	CCONJ
flr-135	418	4	engineering	engineering	NOUN
flr-135	418	5	academy	academy	NOUN
flr-135	418	6	and	and	CCONJ
flr-135	418	7	society	society	NOUN
flr-135	418	8	(	(	PUNCT
flr-135	418	9	wseas	wseas	PROPN
flr-135	418	10	)	)	PUNCT
flr-135	418	11	.	.	PUNCT
flr-135	419	1	stevens	stevens	PROPN
flr-135	419	2	point	point	PROPN
flr-135	419	3	,	,	PUNCT
flr-135	419	4	wisconsin	wisconsin	PROPN
flr-135	419	5	,	,	PUNCT
flr-135	419	6	usa	usa	PROPN
flr-135	419	7	.	.	PROPN
flr-135	419	8	http://dx.doi.org/10.1287/mksc.16.4.370	http://dx.doi.org/10.1287/mksc.16.4.370	PROPN
flr-135	419	9	http://dx.doi.org/10.1287/mksc.16.4.370	http://dx.doi.org/10.1287/mksc.16.4.370	PROPN
flr-135	419	10	http://dx.doi.org/10.1177/0011000006286345	http://dx.doi.org/10.1177/0011000006286345	ADV
flr-135	419	11	http://dx.doi.org/10.1109/72.935080	http://dx.doi.org/10.1109/72.935080	PUNCT
flr-135	419	12	http://dx.doi.org/10.1109/72.935080	http://dx.doi.org/10.1109/72.935080	VERB
flr-135	419	13	http://dx.doi.org/10.1177/0013164495055002003	http://dx.doi.org/10.1177/0013164495055002003	NOUN
flr-135	419	14	http://dx.doi.org/10.1177/0013164495055002003	http://dx.doi.org/10.1177/0013164495055002003	NOUN
flr-135	419	15	http://dx.doi.org/10.1016/j.neucom.2010.01.011	http://dx.doi.org/10.1016/j.neucom.2010.01.011	PROPN
flr-135	419	16	http://dx.doi.org/10.4067/s0718-33052011000300007	http://dx.doi.org/10.4067/s0718-33052011000300007	NOUN