id	sid	tid	token	lemma	pos
flr-74	1	1	frontline	frontline	NOUN
flr-74	1	2	learning	learn	VERB
flr-74	1	3	research	research	NOUN
flr-74	1	4	2	2	NUM
flr-74	1	5	(	(	PUNCT
flr-74	1	6	2013	2013	NUM
flr-74	1	7	)	)	PUNCT
flr-74	1	8	99	99	NUM
flr-74	1	9	-	-	SYM
flr-74	1	10	101	101	NUM
flr-74	1	11	issn	issn	PROPN
flr-74	1	12	2295	2295	NUM
flr-74	1	13	-	-	SYM
flr-74	1	14	3159	3159	NUM
flr-74	1	15	corresponding	corresponding	ADJ
flr-74	1	16	author	author	NOUN
flr-74	1	17	:	:	PUNCT
flr-74	1	18	michael	michael	PROPN
flr-74	1	19	schneider	schneider	PROPN
flr-74	1	20	,	,	PUNCT
flr-74	1	21	university	university	PROPN
flr-74	1	22	of	of	ADP
flr-74	1	23	trier	trier	NOUN
flr-74	1	24	,	,	PUNCT
flr-74	1	25	www.educational-psychology.uni-trier.de	www.educational-psychology.uni-trier.de	PROPN
flr-74	1	26	,	,	PUNCT
flr-74	1	27	m.schneider@uni-trier.de	m.schneider@uni-trier.de	NOUN
flr-74	1	28	,	,	PUNCT
flr-74	1	29	and	and	CCONJ
flr-74	1	30	peter	peter	PROPN
flr-74	1	31	edelsbrunner	edelsbrunner	NOUN
flr-74	1	32	,	,	PUNCT
flr-74	1	33	eth	eth	PROPN
flr-74	1	34	zurich	zurich	PROPN
flr-74	1	35	,	,	PUNCT
flr-74	1	36	www.ifvll.ethz.ch	www.ifvll.ethz.ch	NOUN
flr-74	1	37	,	,	PUNCT
flr-74	1	38	peter.edelsburnner@ifv.gess.ethz.ch	peter.edelsburnner@ifv.gess.ethz.ch	NOUN
flr-74	1	39	http://dx.doi.org/10.14786/flr.v1i2.74	http://dx.doi.org/10.14786/flr.v1i2.74	PROPN
flr-74	1	40	99	99	NUM
flr-74	2	1	|	|	ADV
flr-74	2	2	f	f	NOUN
flr-74	3	1	l	l	NOUN
flr-74	3	2	r	r	NOUN
flr-74	3	3	modelling	modelling	NOUN
flr-74	3	4	for	for	ADP
flr-74	3	5	prediction	prediction	NOUN
flr-74	3	6	vs.	vs.	ADP
flr-74	3	7	modelling	modelling	NOUN
flr-74	3	8	for	for	ADP
flr-74	3	9	understanding	understanding	NOUN
flr-74	3	10	:	:	PUNCT
flr-74	3	11	commentary	commentary	NOUN
flr-74	3	12	on	on	ADP
flr-74	3	13	musso	musso	PROPN
flr-74	3	14	et	et	PROPN
flr-74	3	15	al	al	PROPN
flr-74	3	16	.	.	PROPN
flr-74	4	1	(	(	PUNCT
flr-74	4	2	2013	2013	NUM
flr-74	4	3	)	)	PUNCT
flr-74	4	4	peter	peter	PROPN
flr-74	4	5	edelsbrunner	edelsbrunner	VERB
flr-74	4	6	a	a	PRON
flr-74	4	7	,	,	PUNCT
flr-74	4	8	michael	michael	PROPN
flr-74	4	9	schneider	schneider	PROPN
flr-74	4	10	b	b	PROPN
flr-74	4	11	a	a	DET
flr-74	4	12	eth	eth	PROPN
flr-74	4	13	zurich	zurich	PROPN
flr-74	4	14	,	,	PUNCT
flr-74	4	15	switzerland	switzerland	PROPN
flr-74	4	16	b	b	PROPN
flr-74	4	17	university	university	PROPN
flr-74	4	18	of	of	ADP
flr-74	4	19	trier	trier	NOUN
flr-74	4	20	,	,	PUNCT
flr-74	4	21	germany	germany	PROPN
flr-74	4	22	article	article	NOUN
flr-74	4	23	received	receive	VERB
flr-74	4	24	11	11	NUM
flr-74	4	25	september	september	PROPN
flr-74	4	26	2013	2013	NUM
flr-74	4	27	/	/	PUNCT
flr-74	4	28	accepted	accept	VERB
flr-74	4	29	12	12	NUM
flr-74	4	30	december	december	PROPN
flr-74	4	31	2013	2013	NUM
flr-74	4	32	/	/	SYM
flr-74	4	33	available	available	ADJ
flr-74	4	34	online	online	ADJ
flr-74	4	35	20	20	NUM
flr-74	4	36	december	december	PROPN
flr-74	4	37	2013	2013	NUM
flr-74	4	38	abstract	abstract	ADJ
flr-74	4	39	musso	musso	PROPN
flr-74	4	40	et	et	PROPN
flr-74	4	41	al	al	PROPN
flr-74	4	42	.	.	PROPN
flr-74	5	1	(	(	PUNCT
flr-74	5	2	2013	2013	NUM
flr-74	5	3	)	)	PUNCT
flr-74	5	4	predict	predict	VERB
flr-74	5	5	students	student	NOUN
flr-74	5	6	’	'	PUNCT
flr-74	5	7	academic	academic	ADJ
flr-74	5	8	achievement	achievement	NOUN
flr-74	5	9	with	with	ADP
flr-74	5	10	high	high	ADJ
flr-74	5	11	accuracy	accuracy	NOUN
flr-74	5	12	one	one	NUM
flr-74	5	13	year	year	NOUN
flr-74	5	14	in	in	ADP
flr-74	5	15	advance	advance	NOUN
flr-74	5	16	from	from	ADP
flr-74	5	17	cognitive	cognitive	ADJ
flr-74	5	18	and	and	CCONJ
flr-74	5	19	demographic	demographic	ADJ
flr-74	5	20	variables	variable	NOUN
flr-74	5	21	,	,	PUNCT
flr-74	5	22	using	use	VERB
flr-74	5	23	artificial	artificial	ADJ
flr-74	5	24	neural	neural	ADJ
flr-74	5	25	networks	network	NOUN
flr-74	5	26	(	(	PUNCT
flr-74	5	27	anns	anns	PROPN
flr-74	5	28	)	)	PUNCT
flr-74	5	29	.	.	PUNCT
flr-74	6	1	they	they	PRON
flr-74	6	2	conclude	conclude	VERB
flr-74	6	3	that	that	SCONJ
flr-74	6	4	anns	ann	NOUN
flr-74	6	5	have	have	VERB
flr-74	6	6	high	high	ADJ
flr-74	6	7	potential	potential	NOUN
flr-74	6	8	for	for	ADP
flr-74	6	9	theoretical	theoretical	ADJ
flr-74	6	10	and	and	CCONJ
flr-74	6	11	practical	practical	ADJ
flr-74	6	12	improvements	improvement	NOUN
flr-74	6	13	in	in	ADP
flr-74	6	14	learning	learn	VERB
flr-74	6	15	sciences	science	NOUN
flr-74	6	16	.	.	PUNCT
flr-74	7	1	anns	anns	PROPN
flr-74	7	2	are	be	AUX
flr-74	7	3	powerful	powerful	ADJ
flr-74	7	4	statistical	statistical	ADJ
flr-74	7	5	modelling	modelling	NOUN
flr-74	7	6	tools	tool	NOUN
flr-74	7	7	but	but	CCONJ
flr-74	7	8	they	they	PRON
flr-74	7	9	can	can	AUX
flr-74	7	10	mainly	mainly	ADV
flr-74	7	11	be	be	AUX
flr-74	7	12	used	use	VERB
flr-74	7	13	for	for	ADP
flr-74	7	14	exploratory	exploratory	ADJ
flr-74	7	15	modelling	modelling	NOUN
flr-74	7	16	.	.	PUNCT
flr-74	8	1	moreover	moreover	ADV
flr-74	8	2	,	,	PUNCT
flr-74	8	3	the	the	DET
flr-74	8	4	output	output	NOUN
flr-74	8	5	generated	generate	VERB
flr-74	8	6	from	from	ADP
flr-74	8	7	anns	anns	NOUN
flr-74	8	8	can	can	AUX
flr-74	8	9	not	not	PART
flr-74	8	10	be	be	AUX
flr-74	8	11	fully	fully	ADV
flr-74	8	12	translated	translate	VERB
flr-74	8	13	into	into	ADP
flr-74	8	14	a	a	DET
flr-74	8	15	meaningful	meaningful	ADJ
flr-74	8	16	set	set	NOUN
flr-74	8	17	of	of	ADP
flr-74	8	18	rules	rule	NOUN
flr-74	8	19	because	because	SCONJ
flr-74	8	20	they	they	PRON
flr-74	8	21	store	store	VERB
flr-74	8	22	information	information	NOUN
flr-74	8	23	about	about	ADP
flr-74	8	24	input	input	NOUN
flr-74	8	25	-	-	PUNCT
flr-74	8	26	output	output	NOUN
flr-74	8	27	relations	relation	NOUN
flr-74	8	28	in	in	ADP
flr-74	8	29	a	a	DET
flr-74	8	30	complex	complex	ADJ
flr-74	8	31	,	,	PUNCT
flr-74	8	32	distributed	distribute	VERB
flr-74	8	33	,	,	PUNCT
flr-74	8	34	and	and	CCONJ
flr-74	8	35	implicit	implicit	ADJ
flr-74	8	36	way	way	NOUN
flr-74	8	37	.	.	PUNCT
flr-74	9	1	these	these	DET
flr-74	9	2	problems	problem	NOUN
flr-74	9	3	hamper	hamper	VERB
flr-74	9	4	systematic	systematic	ADJ
flr-74	9	5	theory	theory	NOUN
flr-74	9	6	-	-	PUNCT
flr-74	9	7	building	building	NOUN
flr-74	9	8	as	as	ADV
flr-74	9	9	well	well	ADV
flr-74	9	10	as	as	ADP
flr-74	9	11	communication	communication	NOUN
flr-74	9	12	and	and	CCONJ
flr-74	9	13	justification	justification	NOUN
flr-74	9	14	of	of	ADP
flr-74	9	15	model	model	NOUN
flr-74	9	16	predictions	prediction	NOUN
flr-74	9	17	in	in	ADP
flr-74	9	18	practical	practical	ADJ
flr-74	9	19	contexts	contexts	NOUN
flr-74	9	20	.	.	PUNCT
flr-74	10	1	modern	modern	ADJ
flr-74	10	2	-	-	PUNCT
flr-74	10	3	day	day	NOUN
flr-74	10	4	regression	regression	NOUN
flr-74	10	5	techniques	technique	NOUN
flr-74	10	6	,	,	PUNCT
flr-74	10	7	including	include	VERB
flr-74	10	8	(	(	PUNCT
flr-74	10	9	bayesian	bayesian	NOUN
flr-74	10	10	)	)	PUNCT
flr-74	10	11	structural	structural	ADJ
flr-74	10	12	equation	equation	NOUN
flr-74	10	13	models	model	NOUN
flr-74	10	14	,	,	PUNCT
flr-74	10	15	have	have	VERB
flr-74	10	16	advantages	advantage	NOUN
flr-74	10	17	similar	similar	ADJ
flr-74	10	18	to	to	ADP
flr-74	10	19	those	those	PRON
flr-74	10	20	of	of	ADP
flr-74	10	21	anns	ann	NOUN
flr-74	10	22	but	but	CCONJ
flr-74	10	23	without	without	ADP
flr-74	10	24	the	the	DET
flr-74	10	25	drawbacks	drawback	NOUN
flr-74	10	26	.	.	PUNCT
flr-74	11	1	they	they	PRON
flr-74	11	2	are	be	AUX
flr-74	11	3	able	able	ADJ
flr-74	11	4	to	to	PART
flr-74	11	5	handle	handle	VERB
flr-74	11	6	numerous	numerous	ADJ
flr-74	11	7	variables	variable	NOUN
flr-74	11	8	,	,	PUNCT
flr-74	11	9	non	non	ADJ
flr-74	11	10	-	-	ADJ
flr-74	11	11	linear	linear	ADJ
flr-74	11	12	effects	effect	NOUN
flr-74	11	13	,	,	PUNCT
flr-74	11	14	multi	multi	ADJ
flr-74	11	15	-	-	ADJ
flr-74	11	16	way	way	NOUN
flr-74	11	17	interactions	interaction	NOUN
flr-74	11	18	,	,	PUNCT
flr-74	11	19	and	and	CCONJ
flr-74	11	20	incomplete	incomplete	ADJ
flr-74	11	21	data	datum	NOUN
flr-74	11	22	.	.	PUNCT
flr-74	12	1	thus	thus	ADV
flr-74	12	2	,	,	PUNCT
flr-74	12	3	researchers	researcher	NOUN
flr-74	12	4	in	in	ADP
flr-74	12	5	the	the	DET
flr-74	12	6	learning	learn	VERB
flr-74	12	7	sciences	science	NOUN
flr-74	12	8	should	should	AUX
flr-74	12	9	prefer	prefer	VERB
flr-74	12	10	more	more	ADJ
flr-74	12	11	theory	theory	NOUN
flr-74	12	12	-	-	PUNCT
flr-74	12	13	driven	drive	VERB
flr-74	12	14	and	and	CCONJ
flr-74	12	15	parsimonious	parsimonious	ADJ
flr-74	12	16	modelling	modelling	NOUN
flr-74	12	17	techniques	technique	NOUN
flr-74	12	18	over	over	ADP
flr-74	12	19	anns	anns	NOUN
flr-74	12	20	whenever	whenever	SCONJ
flr-74	12	21	possible	possible	ADJ
flr-74	12	22	.	.	PUNCT
flr-74	13	1	keywords	keyword	NOUN
flr-74	13	2	:	:	PUNCT
flr-74	13	3	artificial	artificial	ADJ
flr-74	13	4	neural	neural	ADJ
flr-74	13	5	networks	network	NOUN
flr-74	13	6	;	;	PUNCT
flr-74	13	7	black	black	ADJ
flr-74	13	8	box	box	NOUN
flr-74	13	9	;	;	PUNCT
flr-74	13	10	student	student	NOUN
flr-74	13	11	achievement	achievement	NOUN
flr-74	13	12	;	;	PUNCT
flr-74	13	13	statistical	statistical	ADJ
flr-74	13	14	modelling	modelling	NOUN
flr-74	13	15	musso	musso	NOUN
flr-74	13	16	,	,	PUNCT
flr-74	13	17	kyndt	kyndt	NOUN
flr-74	13	18	,	,	PUNCT
flr-74	13	19	cascallar	cascallar	ADJ
flr-74	13	20	,	,	PUNCT
flr-74	13	21	and	and	CCONJ
flr-74	13	22	dochy	dochy	NOUN
flr-74	13	23	(	(	PUNCT
flr-74	13	24	2013	2013	NUM
flr-74	13	25	)	)	PUNCT
flr-74	13	26	conducted	conduct	VERB
flr-74	13	27	a	a	DET
flr-74	13	28	study	study	NOUN
flr-74	13	29	in	in	ADP
flr-74	13	30	which	which	PRON
flr-74	13	31	the	the	DET
flr-74	13	32	statistical	statistical	ADJ
flr-74	13	33	modelling	modelling	NOUN
flr-74	13	34	technique	technique	NOUN
flr-74	13	35	of	of	ADP
flr-74	13	36	artificial	artificial	ADJ
flr-74	13	37	neural	neural	ADJ
flr-74	13	38	networks	network	NOUN
flr-74	13	39	(	(	PUNCT
flr-74	13	40	anns	anns	PROPN
flr-74	13	41	)	)	PUNCT
flr-74	13	42	was	be	AUX
flr-74	13	43	used	use	VERB
flr-74	13	44	to	to	PART
flr-74	13	45	predict	predict	VERB
flr-74	13	46	the	the	DET
flr-74	13	47	academic	academic	ADJ
flr-74	13	48	achievement	achievement	NOUN
flr-74	13	49	of	of	ADP
flr-74	13	50	university	university	NOUN
flr-74	13	51	students	student	NOUN
flr-74	13	52	a	a	DET
flr-74	13	53	year	year	NOUN
flr-74	13	54	in	in	ADP
flr-74	13	55	advance	advance	NOUN
flr-74	13	56	.	.	PUNCT
flr-74	14	1	the	the	DET
flr-74	14	2	measures	measure	NOUN
flr-74	14	3	used	use	VERB
flr-74	14	4	were	be	AUX
flr-74	14	5	attention	attention	NOUN
flr-74	14	6	,	,	PUNCT
flr-74	14	7	working	working	NOUN
flr-74	14	8	memory	memory	NOUN
flr-74	14	9	,	,	PUNCT
flr-74	14	10	learning	learning	NOUN
flr-74	14	11	strategies	strategy	NOUN
flr-74	14	12	,	,	PUNCT
flr-74	14	13	and	and	CCONJ
flr-74	14	14	demographic	demographic	ADJ
flr-74	14	15	variables	variable	NOUN
flr-74	14	16	.	.	PUNCT
flr-74	15	1	the	the	DET
flr-74	15	2	results	result	NOUN
flr-74	15	3	were	be	AUX
flr-74	15	4	precise	precise	ADJ
flr-74	15	5	estimations	estimation	NOUN
flr-74	15	6	of	of	ADP
flr-74	15	7	each	each	DET
flr-74	15	8	student	student	NOUN
flr-74	15	9	’s	’s	PART
flr-74	15	10	achievement	achievement	NOUN
flr-74	15	11	tercile	tercile	NOUN
flr-74	15	12	after	after	ADP
flr-74	15	13	their	their	PRON
flr-74	15	14	first	first	ADJ
flr-74	15	15	year	year	NOUN
flr-74	15	16	at	at	ADP
flr-74	15	17	university	university	NOUN
flr-74	15	18	.	.	PUNCT
flr-74	16	1	this	this	PRON
flr-74	16	2	is	be	AUX
flr-74	16	3	an	an	DET
flr-74	16	4	impressive	impressive	ADJ
flr-74	16	5	success	success	NOUN
flr-74	16	6	,	,	PUNCT
flr-74	16	7	demonstrating	demonstrate	VERB
flr-74	16	8	the	the	DET
flr-74	16	9	usefulness	usefulness	NOUN
flr-74	16	10	of	of	ADP
flr-74	16	11	anns	anns	NOUN
flr-74	16	12	as	as	ADP
flr-74	16	13	a	a	DET
flr-74	16	14	statistical	statistical	ADJ
flr-74	16	15	modelling	modelling	NOUN
flr-74	16	16	tool	tool	NOUN
flr-74	16	17	.	.	PUNCT
flr-74	17	1	p.	p.	NOUN
flr-74	17	2	edelsbrunner	edelsbrunner	NOUN
flr-74	17	3	and	and	CCONJ
flr-74	17	4	m.	m.	NOUN
flr-74	17	5	schneider	schneider	PROPN
flr-74	17	6	100	100	NUM
flr-74	18	1	|	|	ADV
flr-74	18	2	f	f	NOUN
flr-74	18	3	l	l	NOUN
flr-74	18	4	r	r	NOUN
flr-74	18	5	the	the	DET
flr-74	18	6	study	study	NOUN
flr-74	18	7	has	have	AUX
flr-74	18	8	raised	raise	VERB
flr-74	18	9	an	an	DET
flr-74	18	10	important	important	ADJ
flr-74	18	11	question	question	NOUN
flr-74	18	12	of	of	ADP
flr-74	18	13	the	the	DET
flr-74	18	14	preferred	preferred	ADJ
flr-74	18	15	statistical	statistical	ADJ
flr-74	18	16	methods	method	NOUN
flr-74	18	17	used	use	VERB
flr-74	18	18	by	by	ADP
flr-74	18	19	researchers	researcher	NOUN
flr-74	18	20	in	in	ADP
flr-74	18	21	learning	learn	VERB
flr-74	18	22	sciences	science	NOUN
flr-74	18	23	.	.	PUNCT
flr-74	19	1	should	should	AUX
flr-74	19	2	anns	anns	NOUN
flr-74	19	3	replace	replace	VERB
flr-74	19	4	conventional	conventional	ADJ
flr-74	19	5	statistical	statistical	ADJ
flr-74	19	6	methods	method	NOUN
flr-74	19	7	such	such	ADJ
flr-74	19	8	as	as	ADP
flr-74	19	9	multiple	multiple	ADJ
flr-74	19	10	regression	regression	NOUN
flr-74	19	11	,	,	PUNCT
flr-74	19	12	discriminant	discriminant	ADJ
flr-74	19	13	analysis	analysis	NOUN
flr-74	19	14	,	,	PUNCT
flr-74	19	15	and	and	CCONJ
flr-74	19	16	structural	structural	ADJ
flr-74	19	17	equation	equation	NOUN
flr-74	19	18	modelling	modelling	NOUN
flr-74	19	19	?	?	PUNCT
flr-74	20	1	–	–	PUNCT
flr-74	20	2	the	the	DET
flr-74	20	3	potential	potential	NOUN
flr-74	20	4	of	of	ADP
flr-74	20	5	anns	anns	NOUN
flr-74	20	6	can	can	AUX
flr-74	20	7	not	not	PART
flr-74	20	8	be	be	AUX
flr-74	20	9	denied	deny	VERB
flr-74	20	10	especially	especially	ADV
flr-74	20	11	as	as	ADP
flr-74	20	12	a	a	DET
flr-74	20	13	tool	tool	NOUN
flr-74	20	14	to	to	PART
flr-74	20	15	examine	examine	VERB
flr-74	20	16	predictive	predictive	ADJ
flr-74	20	17	patterns	pattern	NOUN
flr-74	20	18	in	in	ADP
flr-74	20	19	complex	complex	ADJ
flr-74	20	20	systems	system	NOUN
flr-74	20	21	.	.	PUNCT
flr-74	21	1	however	however	ADV
flr-74	21	2	,	,	PUNCT
flr-74	21	3	musso	musso	PROPN
flr-74	21	4	and	and	CCONJ
flr-74	21	5	colleagues	colleague	NOUN
flr-74	21	6	overestimate	overestimate	VERB
flr-74	21	7	the	the	DET
flr-74	21	8	ability	ability	NOUN
flr-74	21	9	of	of	ADP
flr-74	21	10	anns	anns	NOUN
flr-74	21	11	in	in	ADP
flr-74	21	12	their	their	PRON
flr-74	21	13	application	application	NOUN
flr-74	21	14	to	to	ADP
flr-74	21	15	the	the	DET
flr-74	21	16	learning	learning	NOUN
flr-74	21	17	sciences	science	NOUN
flr-74	21	18	.	.	PUNCT
flr-74	22	1	they	they	PRON
flr-74	22	2	do	do	AUX
flr-74	22	3	not	not	PART
flr-74	22	4	mention	mention	VERB
flr-74	22	5	shortcomings	shortcoming	NOUN
flr-74	22	6	of	of	ADP
flr-74	22	7	anns	ann	NOUN
flr-74	22	8	,	,	PUNCT
flr-74	22	9	while	while	SCONJ
flr-74	22	10	overemphasizing	overemphasize	VERB
flr-74	22	11	shortcomings	shortcoming	NOUN
flr-74	22	12	of	of	ADP
flr-74	22	13	competing	compete	VERB
flr-74	22	14	conventional	conventional	ADJ
flr-74	22	15	methods	method	NOUN
flr-74	22	16	.	.	PUNCT
flr-74	23	1	anns	anns	PROPN
flr-74	23	2	are	be	AUX
flr-74	23	3	limited	limit	VERB
flr-74	23	4	in	in	ADP
flr-74	23	5	at	at	ADV
flr-74	23	6	least	least	ADV
flr-74	23	7	two	two	NUM
flr-74	23	8	important	important	ADJ
flr-74	23	9	ways	way	NOUN
flr-74	23	10	.	.	PUNCT
flr-74	24	1	first	first	ADV
flr-74	24	2	,	,	PUNCT
flr-74	24	3	the	the	DET
flr-74	24	4	construction	construction	NOUN
flr-74	24	5	of	of	ADP
flr-74	24	6	ann	ann	PROPN
flr-74	24	7	models	model	NOUN
flr-74	24	8	such	such	ADJ
flr-74	24	9	as	as	ADP
flr-74	24	10	those	those	PRON
flr-74	24	11	used	use	VERB
flr-74	24	12	by	by	ADP
flr-74	24	13	musso	musso	PROPN
flr-74	24	14	et	et	PROPN
flr-74	24	15	al	al	PROPN
flr-74	24	16	.	.	PROPN
flr-74	24	17	is	be	AUX
flr-74	24	18	highly	highly	ADV
flr-74	24	19	explorative	explorative	ADJ
flr-74	24	20	apart	apart	ADV
flr-74	24	21	from	from	ADP
flr-74	24	22	choosing	choose	VERB
flr-74	24	23	relevant	relevant	ADJ
flr-74	24	24	input	input	NOUN
flr-74	24	25	and	and	CCONJ
flr-74	24	26	output	output	NOUN
flr-74	24	27	variables	variable	NOUN
flr-74	24	28	(	(	PUNCT
flr-74	24	29	günther	günther	NOUN
flr-74	24	30	,	,	PUNCT
flr-74	24	31	pigeot	pigeot	NOUN
flr-74	24	32	,	,	PUNCT
flr-74	24	33	&	&	CCONJ
flr-74	24	34	bammann	bammann	NOUN
flr-74	24	35	,	,	PUNCT
flr-74	24	36	2012	2012	NUM
flr-74	24	37	;	;	PUNCT
flr-74	24	38	scarborough	scarborough	PROPN
flr-74	24	39	&	&	CCONJ
flr-74	24	40	somers	somers	PROPN
flr-74	24	41	,	,	PUNCT
flr-74	24	42	2006	2006	NUM
flr-74	24	43	)	)	PUNCT
flr-74	24	44	.	.	PUNCT
flr-74	25	1	the	the	DET
flr-74	25	2	connection	connection	NOUN
flr-74	25	3	weights	weight	NOUN
flr-74	25	4	,	,	PUNCT
flr-74	25	5	which	which	PRON
flr-74	25	6	determine	determine	VERB
flr-74	25	7	how	how	SCONJ
flr-74	25	8	an	an	DET
flr-74	25	9	ann	ann	PROPN
flr-74	25	10	transforms	transform	VERB
flr-74	25	11	input	input	NOUN
flr-74	25	12	into	into	ADP
flr-74	25	13	output	output	NOUN
flr-74	25	14	patterns	pattern	NOUN
flr-74	25	15	,	,	PUNCT
flr-74	25	16	are	be	AUX
flr-74	25	17	not	not	PART
flr-74	25	18	specified	specify	VERB
flr-74	25	19	by	by	ADP
flr-74	25	20	the	the	DET
flr-74	25	21	researchers	researcher	NOUN
flr-74	25	22	or	or	CCONJ
flr-74	25	23	based	base	VERB
flr-74	25	24	on	on	ADP
flr-74	25	25	theory	theory	NOUN
flr-74	25	26	.	.	PUNCT
flr-74	26	1	they	they	PRON
flr-74	26	2	are	be	AUX
flr-74	26	3	set	set	VERB
flr-74	26	4	to	to	ADP
flr-74	26	5	random	random	ADJ
flr-74	26	6	values	value	NOUN
flr-74	26	7	and	and	CCONJ
flr-74	26	8	changed	change	VERB
flr-74	26	9	gradually	gradually	ADV
flr-74	26	10	by	by	ADP
flr-74	26	11	an	an	DET
flr-74	26	12	optimisation	optimisation	NOUN
flr-74	26	13	algorithm	algorithm	NOUN
flr-74	26	14	.	.	PUNCT
flr-74	27	1	this	this	DET
flr-74	27	2	process	process	NOUN
flr-74	27	3	usually	usually	ADV
flr-74	27	4	involves	involve	VERB
flr-74	27	5	thousands	thousand	NOUN
flr-74	27	6	of	of	ADP
flr-74	27	7	iterations	iteration	NOUN
flr-74	27	8	until	until	SCONJ
flr-74	27	9	each	each	DET
flr-74	27	10	input	input	NOUN
flr-74	27	11	pattern	pattern	NOUN
flr-74	27	12	leads	lead	VERB
flr-74	27	13	to	to	ADP
flr-74	27	14	the	the	DET
flr-74	27	15	desired	desire	VERB
flr-74	27	16	output	output	NOUN
flr-74	27	17	pattern	pattern	NOUN
flr-74	27	18	in	in	ADP
flr-74	27	19	the	the	DET
flr-74	27	20	training	training	NOUN
flr-74	27	21	data	datum	NOUN
flr-74	27	22	set	set	VERB
flr-74	27	23	.	.	PUNCT
flr-74	28	1	anns	anns	PROPN
flr-74	28	2	,	,	PUNCT
flr-74	28	3	thus	thus	ADV
flr-74	28	4	,	,	PUNCT
flr-74	28	5	can	can	AUX
flr-74	28	6	not	not	PART
flr-74	28	7	be	be	AUX
flr-74	28	8	entirely	entirely	ADV
flr-74	28	9	compared	compare	VERB
flr-74	28	10	to	to	ADP
flr-74	28	11	conventional	conventional	ADJ
flr-74	28	12	methods	method	NOUN
flr-74	28	13	since	since	SCONJ
flr-74	28	14	the	the	DET
flr-74	28	15	latter	latter	ADJ
flr-74	28	16	are	be	AUX
flr-74	28	17	aimed	aim	VERB
flr-74	28	18	at	at	ADP
flr-74	28	19	confirming	confirm	VERB
flr-74	28	20	or	or	CCONJ
flr-74	28	21	disconfirming	disconfirme	VERB
flr-74	28	22	pre	pre	ADJ
flr-74	28	23	-	-	ADJ
flr-74	28	24	specified	specified	ADJ
flr-74	28	25	relations	relation	NOUN
flr-74	28	26	and	and	CCONJ
flr-74	28	27	interactions	interaction	NOUN
flr-74	28	28	.	.	PUNCT
flr-74	29	1	in	in	ADP
flr-74	29	2	other	other	ADJ
flr-74	29	3	words	word	NOUN
flr-74	29	4	,	,	PUNCT
flr-74	29	5	the	the	DET
flr-74	29	6	research	research	NOUN
flr-74	29	7	question	question	NOUN
flr-74	29	8	should	should	AUX
flr-74	29	9	determine	determine	VERB
flr-74	29	10	whether	whether	SCONJ
flr-74	29	11	the	the	DET
flr-74	29	12	exploratory	exploratory	ADJ
flr-74	29	13	nature	nature	NOUN
flr-74	29	14	of	of	ADP
flr-74	29	15	anns	anns	NOUN
flr-74	29	16	is	be	AUX
flr-74	29	17	adequate	adequate	ADJ
flr-74	29	18	,	,	PUNCT
flr-74	29	19	or	or	CCONJ
flr-74	29	20	if	if	SCONJ
flr-74	29	21	a	a	DET
flr-74	29	22	conventional	conventional	ADJ
flr-74	29	23	,	,	PUNCT
flr-74	29	24	confirmatory	confirmatory	NOUN
flr-74	29	25	model	model	NOUN
flr-74	29	26	should	should	AUX
flr-74	29	27	be	be	AUX
flr-74	29	28	the	the	DET
flr-74	29	29	method	method	NOUN
flr-74	29	30	of	of	ADP
flr-74	29	31	choice	choice	NOUN
flr-74	29	32	.	.	PUNCT
flr-74	30	1	second	second	ADJ
flr-74	30	2	,	,	PUNCT
flr-74	30	3	connection	connection	NOUN
flr-74	30	4	weights	weight	NOUN
flr-74	30	5	can	can	AUX
flr-74	30	6	not	not	PART
flr-74	30	7	be	be	AUX
flr-74	30	8	codified	codify	VERB
flr-74	30	9	into	into	ADP
flr-74	30	10	a	a	DET
flr-74	30	11	coherent	coherent	ADJ
flr-74	30	12	set	set	NOUN
flr-74	30	13	of	of	ADP
flr-74	30	14	rules	rule	NOUN
flr-74	30	15	that	that	PRON
flr-74	30	16	delineate	delineate	VERB
flr-74	30	17	the	the	DET
flr-74	30	18	process	process	NOUN
flr-74	30	19	by	by	ADP
flr-74	30	20	which	which	PRON
flr-74	30	21	anns	anns	NOUN
flr-74	30	22	transform	transform	VERB
flr-74	30	23	input	input	NOUN
flr-74	30	24	patterns	pattern	NOUN
flr-74	30	25	into	into	ADP
flr-74	30	26	output	output	NOUN
flr-74	30	27	patterns	pattern	NOUN
flr-74	30	28	.	.	PUNCT
flr-74	31	1	anns	anns	PROPN
flr-74	31	2	typically	typically	ADV
flr-74	31	3	have	have	VERB
flr-74	31	4	a	a	DET
flr-74	31	5	high	high	ADJ
flr-74	31	6	number	number	NOUN
flr-74	31	7	of	of	ADP
flr-74	31	8	connections	connection	NOUN
flr-74	31	9	between	between	ADP
flr-74	31	10	neurons	neuron	NOUN
flr-74	31	11	(	(	PUNCT
flr-74	31	12	e.g.	e.g.	ADV
flr-74	31	13	,	,	PUNCT
flr-74	31	14	300	300	NUM
flr-74	31	15	in	in	ADP
flr-74	31	16	ann1	ann1	PROPN
flr-74	31	17	by	by	ADP
flr-74	31	18	musso	musso	PROPN
flr-74	31	19	et	et	PROPN
flr-74	31	20	al	al	PROPN
flr-74	31	21	.	.	PROPN
flr-74	31	22	)	)	PUNCT
flr-74	31	23	.	.	PUNCT
flr-74	32	1	the	the	DET
flr-74	32	2	transformation	transformation	NOUN
flr-74	32	3	process	process	NOUN
flr-74	32	4	of	of	ADP
flr-74	32	5	input	input	NOUN
flr-74	32	6	into	into	ADP
flr-74	32	7	output	output	NOUN
flr-74	32	8	patterns	pattern	NOUN
flr-74	32	9	is	be	AUX
flr-74	32	10	determined	determine	VERB
flr-74	32	11	by	by	ADP
flr-74	32	12	non	non	ADJ
flr-74	32	13	-	-	ADJ
flr-74	32	14	linear	linear	ADJ
flr-74	32	15	,	,	PUNCT
flr-74	32	16	multi	multi	ADJ
flr-74	32	17	-	-	ADJ
flr-74	32	18	way	way	ADJ
flr-74	32	19	interactions	interaction	NOUN
flr-74	32	20	of	of	ADP
flr-74	32	21	these	these	DET
flr-74	32	22	connection	connection	NOUN
flr-74	32	23	weights	weight	NOUN
flr-74	32	24	.	.	PUNCT
flr-74	33	1	recent	recent	ADJ
flr-74	33	2	research	research	NOUN
flr-74	33	3	has	have	AUX
flr-74	33	4	attempted	attempt	VERB
flr-74	33	5	to	to	PART
flr-74	33	6	increase	increase	VERB
flr-74	33	7	the	the	DET
flr-74	33	8	interpretability	interpretability	NOUN
flr-74	33	9	of	of	ADP
flr-74	33	10	anns	ann	NOUN
flr-74	33	11	,	,	PUNCT
flr-74	33	12	for	for	ADP
flr-74	33	13	example	example	NOUN
flr-74	33	14	with	with	ADP
flr-74	33	15	the	the	DET
flr-74	33	16	help	help	NOUN
flr-74	33	17	of	of	ADP
flr-74	33	18	visualizations	visualization	NOUN
flr-74	33	19	for	for	ADP
flr-74	33	20	complex	complex	ADJ
flr-74	33	21	interactions	interaction	NOUN
flr-74	33	22	(	(	PUNCT
flr-74	33	23	e.g.	e.g.	ADV
flr-74	33	24	,	,	PUNCT
flr-74	33	25	cortez	cortez	PROPN
flr-74	33	26	&	&	CCONJ
flr-74	33	27	embrechts	embrecht	NOUN
flr-74	33	28	,	,	PUNCT
flr-74	33	29	2013	2013	NUM
flr-74	33	30	;	;	PUNCT
flr-74	33	31	intrator	intrator	NOUN
flr-74	33	32	&	&	CCONJ
flr-74	33	33	intrator	intrator	PROPN
flr-74	33	34	,	,	PUNCT
flr-74	33	35	2001	2001	NUM
flr-74	33	36	)	)	PUNCT
flr-74	33	37	.	.	PUNCT
flr-74	34	1	however	however	ADV
flr-74	34	2	,	,	PUNCT
flr-74	34	3	the	the	DET
flr-74	34	4	basic	basic	ADJ
flr-74	34	5	problem	problem	NOUN
flr-74	34	6	of	of	ADP
flr-74	34	7	how	how	SCONJ
flr-74	34	8	non	non	ADJ
flr-74	34	9	-	-	ADJ
flr-74	34	10	linear	linear	ADJ
flr-74	34	11	interactions	interaction	NOUN
flr-74	34	12	between	between	ADP
flr-74	34	13	hundreds	hundred	NOUN
flr-74	34	14	of	of	ADP
flr-74	34	15	variables	variable	NOUN
flr-74	34	16	can	can	AUX
flr-74	34	17	be	be	AUX
flr-74	34	18	understood	understand	VERB
flr-74	34	19	and	and	CCONJ
flr-74	34	20	communicated	communicate	VERB
flr-74	34	21	in	in	ADP
flr-74	34	22	meaningful	meaningful	ADJ
flr-74	34	23	terms	term	NOUN
flr-74	34	24	has	have	AUX
flr-74	34	25	not	not	PART
flr-74	34	26	yet	yet	ADV
flr-74	34	27	been	be	AUX
flr-74	34	28	solved	solve	VERB
flr-74	34	29	,	,	PUNCT
flr-74	34	30	causing	cause	VERB
flr-74	34	31	anns	ann	NOUN
flr-74	34	32	to	to	PART
flr-74	34	33	be	be	AUX
flr-74	34	34	frequently	frequently	ADV
flr-74	34	35	characterised	characterise	VERB
flr-74	34	36	as	as	ADP
flr-74	34	37	“	"	PUNCT
flr-74	34	38	black	black	ADJ
flr-74	34	39	boxes	box	NOUN
flr-74	34	40	”	"	PUNCT
flr-74	34	41	(	(	PUNCT
flr-74	34	42	cf	cf	NOUN
flr-74	34	43	.	.	PUNCT
flr-74	35	1	benitez	benitez	PROPN
flr-74	35	2	,	,	PUNCT
flr-74	35	3	castro	castro	PROPN
flr-74	35	4	,	,	PUNCT
flr-74	35	5	&	&	CCONJ
flr-74	35	6	requena	requena	NOUN
flr-74	35	7	,	,	PUNCT
flr-74	35	8	1997	1997	NUM
flr-74	35	9	)	)	PUNCT
flr-74	35	10	.	.	PUNCT
flr-74	36	1	while	while	SCONJ
flr-74	36	2	one	one	PRON
flr-74	36	3	can	can	AUX
flr-74	36	4	assess	assess	VERB
flr-74	36	5	how	how	SCONJ
flr-74	36	6	well	well	ADV
flr-74	36	7	an	an	DET
flr-74	36	8	ann	ann	PROPN
flr-74	36	9	works	work	NOUN
flr-74	36	10	,	,	PUNCT
flr-74	36	11	it	it	PRON
flr-74	36	12	is	be	AUX
flr-74	36	13	difficult	difficult	ADJ
flr-74	36	14	to	to	PART
flr-74	36	15	comprehensively	comprehensively	ADV
flr-74	36	16	explain	explain	VERB
flr-74	36	17	why	why	SCONJ
flr-74	36	18	it	it	PRON
flr-74	36	19	performs	perform	VERB
flr-74	36	20	well	well	ADV
flr-74	36	21	or	or	CCONJ
flr-74	36	22	not	not	PART
flr-74	36	23	(	(	PUNCT
flr-74	36	24	scarborough	scarborough	PROPN
flr-74	36	25	&	&	CCONJ
flr-74	36	26	somers	somers	PROPN
flr-74	36	27	,	,	PUNCT
flr-74	36	28	2006	2006	NUM
flr-74	36	29	)	)	PUNCT
flr-74	36	30	.	.	PUNCT
flr-74	37	1	to	to	PART
flr-74	37	2	interpret	interpret	VERB
flr-74	37	3	their	their	PRON
flr-74	37	4	results	result	NOUN
flr-74	37	5	,	,	PUNCT
flr-74	37	6	musso	musso	PROPN
flr-74	37	7	and	and	CCONJ
flr-74	37	8	colleagues	colleague	NOUN
flr-74	37	9	list	list	VERB
flr-74	37	10	an	an	DET
flr-74	37	11	importance	importance	NOUN
flr-74	37	12	parameter	parameter	NOUN
flr-74	37	13	for	for	ADP
flr-74	37	14	each	each	DET
flr-74	37	15	predictor	predictor	NOUN
flr-74	37	16	but	but	CCONJ
flr-74	37	17	these	these	DET
flr-74	37	18	parameters	parameter	NOUN
flr-74	37	19	do	do	AUX
flr-74	37	20	not	not	PART
flr-74	37	21	explain	explain	VERB
flr-74	37	22	interaction	interaction	NOUN
flr-74	37	23	effects	effect	NOUN
flr-74	37	24	or	or	CCONJ
flr-74	37	25	non	non	ADJ
flr-74	37	26	-	-	ADJ
flr-74	37	27	linear	linear	ADJ
flr-74	37	28	relations	relation	NOUN
flr-74	37	29	among	among	ADP
flr-74	37	30	the	the	DET
flr-74	37	31	variables	variable	NOUN
flr-74	37	32	.	.	PUNCT
flr-74	38	1	in	in	ADP
flr-74	38	2	addition	addition	NOUN
flr-74	38	3	,	,	PUNCT
flr-74	38	4	it	it	PRON
flr-74	38	5	is	be	AUX
flr-74	38	6	difficult	difficult	ADJ
flr-74	38	7	to	to	PART
flr-74	38	8	integrate	integrate	VERB
flr-74	38	9	the	the	DET
flr-74	38	10	results	result	NOUN
flr-74	38	11	of	of	ADP
flr-74	38	12	anns	anns	NOUN
flr-74	38	13	across	across	ADP
flr-74	38	14	studies	study	NOUN
flr-74	38	15	and	and	CCONJ
flr-74	38	16	also	also	ADV
flr-74	38	17	generalise	generalise	VERB
flr-74	38	18	from	from	ADP
flr-74	38	19	samples	sample	NOUN
flr-74	38	20	to	to	ADP
flr-74	38	21	underlying	underlie	VERB
flr-74	38	22	populations	population	NOUN
flr-74	38	23	due	due	ADP
flr-74	38	24	to	to	ADP
flr-74	38	25	the	the	DET
flr-74	38	26	lack	lack	NOUN
flr-74	38	27	of	of	ADP
flr-74	38	28	output	output	NOUN
flr-74	38	29	parameters	parameter	NOUN
flr-74	38	30	such	such	ADJ
flr-74	38	31	as	as	ADP
flr-74	38	32	standard	standard	ADJ
flr-74	38	33	errors	error	NOUN
flr-74	38	34	and	and	CCONJ
flr-74	38	35	error	error	NOUN
flr-74	38	36	probabilities	probability	NOUN
flr-74	38	37	.	.	PUNCT
flr-74	39	1	the	the	DET
flr-74	39	2	explorative	explorative	ADJ
flr-74	39	3	and	and	CCONJ
flr-74	39	4	opaque	opaque	ADJ
flr-74	39	5	nature	nature	NOUN
flr-74	39	6	of	of	ADP
flr-74	39	7	anns	anns	NOUN
flr-74	39	8	impedes	impede	VERB
flr-74	39	9	theory	theory	NOUN
flr-74	39	10	-	-	PUNCT
flr-74	39	11	developing	develop	VERB
flr-74	39	12	and	and	CCONJ
flr-74	39	13	limits	limit	VERB
flr-74	39	14	their	their	PRON
flr-74	39	15	practical	practical	ADJ
flr-74	39	16	application	application	NOUN
flr-74	39	17	.	.	PUNCT
flr-74	40	1	each	each	DET
flr-74	40	2	relation	relation	NOUN
flr-74	40	3	in	in	ADP
flr-74	40	4	a	a	DET
flr-74	40	5	statistical	statistical	ADJ
flr-74	40	6	model	model	NOUN
flr-74	40	7	should	should	AUX
flr-74	40	8	ideally	ideally	ADV
flr-74	40	9	correspond	correspond	VERB
flr-74	40	10	to	to	ADP
flr-74	40	11	a	a	DET
flr-74	40	12	matching	matching	NOUN
flr-74	40	13	relation	relation	NOUN
flr-74	40	14	in	in	ADP
flr-74	40	15	an	an	DET
flr-74	40	16	educational	educational	ADJ
flr-74	40	17	or	or	CCONJ
flr-74	40	18	psychological	psychological	ADJ
flr-74	40	19	theory	theory	NOUN
flr-74	40	20	that	that	PRON
flr-74	40	21	justifies	justify	VERB
flr-74	40	22	and	and	CCONJ
flr-74	40	23	explains	explain	VERB
flr-74	40	24	the	the	DET
flr-74	40	25	assumed	assumed	ADJ
flr-74	40	26	statistical	statistical	ADJ
flr-74	40	27	relation	relation	NOUN
flr-74	40	28	.	.	PUNCT
flr-74	41	1	researchers	researcher	NOUN
flr-74	41	2	can	can	AUX
flr-74	41	3	compare	compare	VERB
flr-74	41	4	competing	compete	VERB
flr-74	41	5	theories	theory	NOUN
flr-74	41	6	and	and	CCONJ
flr-74	41	7	advance	advance	NOUN
flr-74	41	8	assumptions	assumption	NOUN
flr-74	41	9	that	that	PRON
flr-74	41	10	are	be	AUX
flr-74	41	11	not	not	PART
flr-74	41	12	in	in	ADP
flr-74	41	13	line	line	NOUN
flr-74	41	14	with	with	ADP
flr-74	41	15	the	the	DET
flr-74	41	16	empirical	empirical	ADJ
flr-74	41	17	data	datum	NOUN
flr-74	41	18	by	by	ADP
flr-74	41	19	fitting	fit	VERB
flr-74	41	20	a	a	DET
flr-74	41	21	series	series	NOUN
flr-74	41	22	of	of	ADP
flr-74	41	23	statistical	statistical	ADJ
flr-74	41	24	models	model	NOUN
flr-74	41	25	that	that	PRON
flr-74	41	26	differ	differ	VERB
flr-74	41	27	in	in	ADP
flr-74	41	28	theoretically	theoretically	ADV
flr-74	41	29	relevant	relevant	ADJ
flr-74	41	30	aspects	aspect	NOUN
flr-74	41	31	(	(	PUNCT
flr-74	41	32	kaplan	kaplan	NOUN
flr-74	41	33	,	,	PUNCT
flr-74	41	34	1990	1990	NUM
flr-74	41	35	)	)	PUNCT
flr-74	41	36	.	.	PUNCT
flr-74	42	1	this	this	PRON
flr-74	42	2	is	be	AUX
flr-74	42	3	not	not	PART
flr-74	42	4	possible	possible	ADJ
flr-74	42	5	with	with	ADP
flr-74	42	6	anns	ann	NOUN
flr-74	42	7	because	because	SCONJ
flr-74	42	8	the	the	DET
flr-74	42	9	input	input	NOUN
flr-74	42	10	-	-	PUNCT
flr-74	42	11	output	output	NOUN
flr-74	42	12	relations	relation	NOUN
flr-74	42	13	are	be	AUX
flr-74	42	14	implicitly	implicitly	ADV
flr-74	42	15	coded	code	VERB
flr-74	42	16	and	and	CCONJ
flr-74	42	17	distributed	distribute	VERB
flr-74	42	18	over	over	ADP
flr-74	42	19	all	all	DET
flr-74	42	20	connection	connection	NOUN
flr-74	42	21	weights	weight	NOUN
flr-74	42	22	,	,	PUNCT
flr-74	42	23	preventing	prevent	VERB
flr-74	42	24	researchers	researcher	NOUN
flr-74	42	25	from	from	ADP
flr-74	42	26	being	be	AUX
flr-74	42	27	able	able	ADJ
flr-74	42	28	to	to	PART
flr-74	42	29	map	map	VERB
flr-74	42	30	elements	element	NOUN
flr-74	42	31	of	of	ADP
flr-74	42	32	an	an	DET
flr-74	42	33	ann	ann	NOUN
flr-74	42	34	and	and	CCONJ
flr-74	42	35	elements	element	NOUN
flr-74	42	36	of	of	ADP
flr-74	42	37	a	a	DET
flr-74	42	38	theory	theory	NOUN
flr-74	42	39	onto	onto	ADP
flr-74	42	40	each	each	DET
flr-74	42	41	other	other	ADJ
flr-74	42	42	(	(	PUNCT
flr-74	42	43	luger	luger	NOUN
flr-74	42	44	,	,	PUNCT
flr-74	42	45	2009	2009	NUM
flr-74	42	46	,	,	PUNCT
flr-74	42	47	p.	p.	NOUN
flr-74	42	48	680	680	NUM
flr-74	42	49	)	)	PUNCT
flr-74	42	50	.	.	PUNCT
flr-74	43	1	the	the	DET
flr-74	43	2	results	result	NOUN
flr-74	43	3	obtained	obtain	VERB
flr-74	43	4	from	from	ADP
flr-74	43	5	ann	ann	PROPN
flr-74	43	6	models	model	NOUN
flr-74	43	7	are	be	AUX
flr-74	43	8	also	also	ADV
flr-74	43	9	of	of	ADP
flr-74	43	10	limited	limited	ADJ
flr-74	43	11	use	use	NOUN
flr-74	43	12	for	for	ADP
flr-74	43	13	solving	solve	VERB
flr-74	43	14	real	real	ADJ
flr-74	43	15	-	-	PUNCT
flr-74	43	16	life	life	NOUN
flr-74	43	17	problems	problem	NOUN
flr-74	43	18	.	.	PUNCT
flr-74	44	1	this	this	DET
flr-74	44	2	limitation	limitation	NOUN
flr-74	44	3	can	can	AUX
flr-74	44	4	be	be	AUX
flr-74	44	5	illustrated	illustrate	VERB
flr-74	44	6	in	in	ADP
flr-74	44	7	a	a	DET
flr-74	44	8	situation	situation	NOUN
flr-74	44	9	where	where	SCONJ
flr-74	44	10	diagnosticians	diagnostician	NOUN
flr-74	44	11	would	would	AUX
flr-74	44	12	have	have	VERB
flr-74	44	13	to	to	PART
flr-74	44	14	tell	tell	VERB
flr-74	44	15	certain	certain	ADJ
flr-74	44	16	high	high	ADJ
flr-74	44	17	school	school	NOUN
flr-74	44	18	students	student	NOUN
flr-74	44	19	that	that	SCONJ
flr-74	44	20	despite	despite	SCONJ
flr-74	44	21	achieving	achieve	VERB
flr-74	44	22	satisfactory	satisfactory	ADJ
flr-74	44	23	levels	level	NOUN
flr-74	44	24	in	in	ADP
flr-74	44	25	their	their	PRON
flr-74	44	26	current	current	ADJ
flr-74	44	27	academic	academic	ADJ
flr-74	44	28	performances	performance	NOUN
flr-74	44	29	,	,	PUNCT
flr-74	44	30	they	they	PRON
flr-74	44	31	can	can	AUX
flr-74	44	32	not	not	PART
flr-74	44	33	be	be	AUX
flr-74	44	34	admitted	admit	VERB
flr-74	44	35	to	to	ADP
flr-74	44	36	college	college	NOUN
flr-74	44	37	because	because	SCONJ
flr-74	44	38	an	an	DET
flr-74	44	39	ann	ann	PROPN
flr-74	44	40	predicts	predict	VERB
flr-74	44	41	low	low	ADJ
flr-74	44	42	academic	academic	ADJ
flr-74	44	43	performance	performance	NOUN
flr-74	44	44	in	in	ADP
flr-74	44	45	the	the	DET
flr-74	44	46	future	future	NOUN
flr-74	44	47	.	.	PUNCT
flr-74	45	1	in	in	ADP
flr-74	45	2	justifying	justify	VERB
flr-74	45	3	the	the	DET
flr-74	45	4	results	result	NOUN
flr-74	45	5	,	,	PUNCT
flr-74	45	6	the	the	DET
flr-74	45	7	diagnosticians	diagnosticians	PROPN
flr-74	45	8	would	would	AUX
flr-74	45	9	have	have	VERB
flr-74	45	10	to	to	PART
flr-74	45	11	admit	admit	VERB
flr-74	45	12	that	that	SCONJ
flr-74	45	13	they	they	PRON
flr-74	45	14	can	can	AUX
flr-74	45	15	not	not	PART
flr-74	45	16	explain	explain	VERB
flr-74	45	17	how	how	SCONJ
flr-74	45	18	the	the	DET
flr-74	45	19	different	different	ADJ
flr-74	45	20	predictors	predictor	NOUN
flr-74	45	21	statistically	statistically	ADV
flr-74	45	22	combine	combine	VERB
flr-74	45	23	,	,	PUNCT
flr-74	45	24	nor	nor	CCONJ
flr-74	45	25	describe	describe	VERB
flr-74	45	26	the	the	DET
flr-74	45	27	causal	causal	NOUN
flr-74	45	28	processes	process	NOUN
flr-74	45	29	that	that	PRON
flr-74	45	30	will	will	AUX
flr-74	45	31	contribute	contribute	VERB
flr-74	45	32	to	to	ADP
flr-74	45	33	the	the	DET
flr-74	45	34	anticipated	anticipate	VERB
flr-74	45	35	decrease	decrease	NOUN
flr-74	45	36	in	in	ADP
flr-74	45	37	the	the	DET
flr-74	45	38	students	student	NOUN
flr-74	45	39	’	'	PUNCT
flr-74	45	40	achievement	achievement	NOUN
flr-74	45	41	.	.	PUNCT
flr-74	46	1	these	these	DET
flr-74	46	2	limitations	limitation	NOUN
flr-74	46	3	are	be	AUX
flr-74	46	4	unsatisfactory	unsatisfactory	ADJ
flr-74	46	5	from	from	ADP
flr-74	46	6	diagnostic	diagnostic	ADJ
flr-74	46	7	,	,	PUNCT
flr-74	46	8	educational	educational	ADJ
flr-74	46	9	,	,	PUNCT
flr-74	46	10	and	and	CCONJ
flr-74	46	11	public	public	ADJ
flr-74	46	12	policymaking	policymaking	ADJ
flr-74	46	13	perspectives	perspective	NOUN
flr-74	46	14	.	.	PUNCT
flr-74	47	1	conventional	conventional	ADJ
flr-74	47	2	methods	method	NOUN
flr-74	47	3	represent	represent	VERB
flr-74	47	4	more	more	ADV
flr-74	47	5	parsimonious	parsimonious	ADJ
flr-74	47	6	and	and	CCONJ
flr-74	47	7	theory	theory	NOUN
flr-74	47	8	-	-	PUNCT
flr-74	47	9	driven	drive	VERB
flr-74	47	10	alternatives	alternative	NOUN
flr-74	47	11	to	to	ADP
flr-74	47	12	anns	ann	NOUN
flr-74	47	13	because	because	SCONJ
flr-74	47	14	they	they	PRON
flr-74	47	15	use	use	VERB
flr-74	47	16	smaller	small	ADJ
flr-74	47	17	numbers	number	NOUN
flr-74	47	18	of	of	ADP
flr-74	47	19	parameters	parameter	NOUN
flr-74	47	20	,	,	PUNCT
flr-74	47	21	which	which	PRON
flr-74	47	22	enhances	enhance	VERB
flr-74	47	23	the	the	DET
flr-74	47	24	interpretability	interpretability	NOUN
flr-74	47	25	of	of	ADP
flr-74	47	26	results	result	NOUN
flr-74	47	27	.	.	PUNCT
flr-74	48	1	like	like	ADP
flr-74	48	2	anns	ann	NOUN
flr-74	48	3	,	,	PUNCT
flr-74	48	4	modern	modern	ADJ
flr-74	48	5	regression	regression	NOUN
flr-74	48	6	techniques	technique	NOUN
flr-74	48	7	can	can	AUX
flr-74	48	8	account	account	VERB
flr-74	48	9	for	for	ADP
flr-74	48	10	non	non	ADJ
flr-74	48	11	-	-	ADJ
flr-74	48	12	linear	linear	ADJ
flr-74	48	13	relations	relation	NOUN
flr-74	48	14	(	(	PUNCT
flr-74	48	15	bates	bate	NOUN
flr-74	48	16	&	&	CCONJ
flr-74	48	17	watts	watts	PROPN
flr-74	48	18	,	,	PUNCT
flr-74	48	19	2007	2007	NUM
flr-74	48	20	)	)	PUNCT
flr-74	48	21	and	and	CCONJ
flr-74	48	22	complex	complex	ADJ
flr-74	48	23	interactions	interaction	NOUN
flr-74	48	24	between	between	ADP
flr-74	48	25	variables	variable	NOUN
flr-74	48	26	(	(	PUNCT
flr-74	48	27	aiken	aiken	PROPN
flr-74	48	28	&	&	CCONJ
flr-74	48	29	west	west	PROPN
flr-74	48	30	,	,	PUNCT
flr-74	48	31	1991	1991	NUM
flr-74	48	32	)	)	PUNCT
flr-74	48	33	.	.	PUNCT
flr-74	49	1	structural	structural	ADJ
flr-74	49	2	equation	equation	NOUN
flr-74	49	3	models	model	NOUN
flr-74	49	4	are	be	AUX
flr-74	49	5	built	build	VERB
flr-74	49	6	on	on	ADP
flr-74	49	7	regression	regression	NOUN
flr-74	49	8	techniques	technique	NOUN
flr-74	49	9	and	and	CCONJ
flr-74	49	10	p.	p.	NOUN
flr-74	49	11	edelsbrunner	edelsbrunner	NOUN
flr-74	49	12	and	and	CCONJ
flr-74	49	13	m.	m.	NOUN
flr-74	49	14	schneider	schneider	NOUN
flr-74	49	15	101	101	NUM
flr-74	50	1	|	|	NOUN
flr-74	50	2	f	f	NOUN
flr-74	50	3	l	l	NOUN
flr-74	50	4	r	r	NOUN
flr-74	50	5	allow	allow	VERB
flr-74	50	6	a	a	DET
flr-74	50	7	simultaneous	simultaneous	ADJ
flr-74	50	8	analysis	analysis	NOUN
flr-74	50	9	of	of	ADP
flr-74	50	10	numerous	numerous	ADJ
flr-74	50	11	variables	variable	NOUN
flr-74	50	12	.	.	PUNCT
flr-74	51	1	these	these	DET
flr-74	51	2	models	model	NOUN
flr-74	51	3	can	can	AUX
flr-74	51	4	be	be	AUX
flr-74	51	5	estimated	estimate	VERB
flr-74	51	6	by	by	ADP
flr-74	51	7	methods	method	NOUN
flr-74	51	8	that	that	PRON
flr-74	51	9	are	be	AUX
flr-74	51	10	robust	robust	ADJ
flr-74	51	11	to	to	ADP
flr-74	51	12	missing	miss	VERB
flr-74	51	13	data	datum	NOUN
flr-74	51	14	and	and	CCONJ
flr-74	51	15	non	non	ADJ
flr-74	51	16	-	-	ADJ
flr-74	51	17	normal	normal	ADJ
flr-74	51	18	distributions	distribution	NOUN
flr-74	51	19	,	,	PUNCT
flr-74	51	20	account	account	VERB
flr-74	51	21	for	for	ADP
flr-74	51	22	hierarchical	hierarchical	ADJ
flr-74	51	23	data	datum	NOUN
flr-74	51	24	structures	structure	NOUN
flr-74	51	25	,	,	PUNCT
flr-74	51	26	and	and	CCONJ
flr-74	51	27	identify	identify	VERB
flr-74	51	28	heterogeneous	heterogeneous	ADJ
flr-74	51	29	sub	sub	NOUN
flr-74	51	30	-	-	NOUN
flr-74	51	31	populations	population	NOUN
flr-74	51	32	in	in	ADP
flr-74	51	33	mixture	mixture	NOUN
flr-74	51	34	-	-	PUNCT
flr-74	51	35	models	model	NOUN
flr-74	51	36	(	(	PUNCT
flr-74	51	37	hoyle	hoyle	NOUN
flr-74	51	38	,	,	PUNCT
flr-74	51	39	2012	2012	NUM
flr-74	51	40	)	)	PUNCT
flr-74	51	41	.	.	PUNCT
flr-74	52	1	especially	especially	ADV
flr-74	52	2	bayesian	bayesian	VERB
flr-74	52	3	structural	structural	ADJ
flr-74	52	4	equation	equation	NOUN
flr-74	52	5	models	model	NOUN
flr-74	52	6	represent	represent	VERB
flr-74	52	7	a	a	DET
flr-74	52	8	strong	strong	ADJ
flr-74	52	9	advancement	advancement	NOUN
flr-74	52	10	in	in	ADP
flr-74	52	11	modelling	model	VERB
flr-74	52	12	non	non	ADJ
flr-74	52	13	-	-	ADJ
flr-74	52	14	linear	linear	ADJ
flr-74	52	15	relations	relation	NOUN
flr-74	52	16	,	,	PUNCT
flr-74	52	17	assessing	assess	VERB
flr-74	52	18	unspecified	unspecified	ADJ
flr-74	52	19	relations	relation	NOUN
flr-74	52	20	and	and	CCONJ
flr-74	52	21	handling	handle	VERB
flr-74	52	22	highly	highly	ADV
flr-74	52	23	non	non	ADJ
flr-74	52	24	-	-	ADJ
flr-74	52	25	normal	normal	ADJ
flr-74	52	26	and	and	CCONJ
flr-74	52	27	hierarchical	hierarchical	ADJ
flr-74	52	28	data	datum	NOUN
flr-74	52	29	(	(	PUNCT
flr-74	52	30	song	song	NOUN
flr-74	52	31	&	&	CCONJ
flr-74	52	32	lee	lee	PROPN
flr-74	52	33	,	,	PUNCT
flr-74	52	34	2012	2012	NUM
flr-74	52	35	)	)	PUNCT
flr-74	52	36	.	.	PUNCT
flr-74	53	1	in	in	ADP
flr-74	53	2	contrast	contrast	NOUN
flr-74	53	3	to	to	ADP
flr-74	53	4	anns	ann	NOUN
flr-74	53	5	,	,	PUNCT
flr-74	53	6	these	these	PRON
flr-74	53	7	modelling	model	VERB
flr-74	53	8	techniques	technique	NOUN
flr-74	53	9	require	require	VERB
flr-74	53	10	explicit	explicit	ADJ
flr-74	53	11	theoretical	theoretical	ADJ
flr-74	53	12	assumptions	assumption	NOUN
flr-74	53	13	about	about	ADP
flr-74	53	14	the	the	DET
flr-74	53	15	relationship	relationship	NOUN
flr-74	53	16	of	of	ADP
flr-74	53	17	the	the	DET
flr-74	53	18	variables	variable	NOUN
flr-74	53	19	and	and	CCONJ
flr-74	53	20	they	they	PRON
flr-74	53	21	allow	allow	VERB
flr-74	53	22	for	for	ADP
flr-74	53	23	explicit	explicit	ADJ
flr-74	53	24	tests	test	NOUN
flr-74	53	25	of	of	ADP
flr-74	53	26	these	these	DET
flr-74	53	27	assumptions	assumption	NOUN
flr-74	53	28	.	.	PUNCT
flr-74	54	1	this	this	PRON
flr-74	54	2	might	might	AUX
flr-74	54	3	limit	limit	VERB
flr-74	54	4	their	their	PRON
flr-74	54	5	predictive	predictive	ADJ
flr-74	54	6	power	power	NOUN
flr-74	54	7	compared	compare	VERB
flr-74	54	8	to	to	ADP
flr-74	54	9	anns	ann	NOUN
flr-74	54	10	,	,	PUNCT
flr-74	54	11	but	but	CCONJ
flr-74	54	12	it	it	PRON
flr-74	54	13	aids	aid	VERB
flr-74	54	14	theory	theory	NOUN
flr-74	54	15	-	-	PUNCT
flr-74	54	16	building	building	NOUN
flr-74	54	17	,	,	PUNCT
flr-74	54	18	hypothesis	hypothesis	NOUN
flr-74	54	19	testing	testing	NOUN
flr-74	54	20	,	,	PUNCT
flr-74	54	21	and	and	CCONJ
flr-74	54	22	the	the	DET
flr-74	54	23	communication	communication	NOUN
flr-74	54	24	of	of	ADP
flr-74	54	25	model	model	NOUN
flr-74	54	26	results	result	NOUN
flr-74	54	27	in	in	ADP
flr-74	54	28	practical	practical	ADJ
flr-74	54	29	applications	application	NOUN
flr-74	54	30	.	.	PUNCT
flr-74	55	1	keypoints	keypoint	NOUN
flr-74	55	2	artificial	artificial	ADJ
flr-74	55	3	neural	neural	ADJ
flr-74	55	4	networks	network	NOUN
flr-74	55	5	are	be	AUX
flr-74	55	6	powerful	powerful	ADJ
flr-74	55	7	statistical	statistical	ADJ
flr-74	55	8	tools	tool	NOUN
flr-74	55	9	for	for	ADP
flr-74	55	10	pattern	pattern	NOUN
flr-74	55	11	recognition	recognition	NOUN
flr-74	55	12	and	and	CCONJ
flr-74	55	13	prediction	prediction	NOUN
flr-74	55	14	.	.	PUNCT
flr-74	56	1	artificial	artificial	ADJ
flr-74	56	2	neural	neural	ADJ
flr-74	56	3	networks	network	NOUN
flr-74	56	4	transform	transform	VERB
flr-74	56	5	input	input	NOUN
flr-74	56	6	patterns	pattern	NOUN
flr-74	56	7	into	into	ADP
flr-74	56	8	output	output	NOUN
flr-74	56	9	patterns	pattern	NOUN
flr-74	56	10	by	by	ADP
flr-74	56	11	non	non	ADJ
flr-74	56	12	-	-	ADJ
flr-74	56	13	linear	linear	ADJ
flr-74	56	14	multi	multi	ADJ
flr-74	56	15	-	-	ADJ
flr-74	56	16	way	way	NOUN
flr-74	56	17	interactions	interaction	NOUN
flr-74	56	18	between	between	ADP
flr-74	56	19	simulated	simulated	ADJ
flr-74	56	20	neurons	neuron	NOUN
flr-74	56	21	that	that	PRON
flr-74	56	22	are	be	AUX
flr-74	56	23	governed	govern	VERB
flr-74	56	24	by	by	ADP
flr-74	56	25	information	information	NOUN
flr-74	56	26	that	that	PRON
flr-74	56	27	is	be	AUX
flr-74	56	28	stored	store	VERB
flr-74	56	29	in	in	ADP
flr-74	56	30	connection	connection	NOUN
flr-74	56	31	weights	weight	NOUN
flr-74	56	32	in	in	ADP
flr-74	56	33	an	an	DET
flr-74	56	34	implicit	implicit	ADJ
flr-74	56	35	and	and	CCONJ
flr-74	56	36	distributed	distribute	VERB
flr-74	56	37	way	way	NOUN
flr-74	56	38	.	.	PUNCT
flr-74	57	1	this	this	DET
flr-74	57	2	“	"	PUNCT
flr-74	57	3	black	black	ADJ
flr-74	57	4	box	box	NOUN
flr-74	57	5	”	"	PUNCT
flr-74	57	6	nature	nature	NOUN
flr-74	57	7	of	of	ADP
flr-74	57	8	artificial	artificial	ADJ
flr-74	57	9	neural	neural	ADJ
flr-74	57	10	networks	network	NOUN
flr-74	57	11	hampers	hamper	VERB
flr-74	57	12	the	the	DET
flr-74	57	13	systematic	systematic	ADJ
flr-74	57	14	testing	testing	NOUN
flr-74	57	15	of	of	ADP
flr-74	57	16	theories	theory	NOUN
flr-74	57	17	and	and	CCONJ
flr-74	57	18	the	the	DET
flr-74	57	19	communication	communication	NOUN
flr-74	57	20	of	of	ADP
flr-74	57	21	results	result	NOUN
flr-74	57	22	in	in	ADP
flr-74	57	23	practical	practical	ADJ
flr-74	57	24	settings	setting	NOUN
flr-74	57	25	.	.	PUNCT
flr-74	58	1	more	more	ADJ
flr-74	58	2	conventional	conventional	ADJ
flr-74	58	3	regression	regression	NOUN
flr-74	58	4	-	-	PUNCT
flr-74	58	5	type	type	NOUN
flr-74	58	6	models	model	NOUN
flr-74	58	7	can	can	AUX
flr-74	58	8	also	also	ADV
flr-74	58	9	handle	handle	VERB
flr-74	58	10	non	non	ADJ
flr-74	58	11	-	-	ADJ
flr-74	58	12	linear	linear	ADJ
flr-74	58	13	relations	relation	NOUN
flr-74	58	14	,	,	PUNCT
flr-74	58	15	interaction	interaction	NOUN
flr-74	58	16	effects	effect	NOUN
flr-74	58	17	,	,	PUNCT
flr-74	58	18	and	and	CCONJ
flr-74	58	19	a	a	DET
flr-74	58	20	high	high	ADJ
flr-74	58	21	number	number	NOUN
flr-74	58	22	of	of	ADP
flr-74	58	23	variables	variable	NOUN
flr-74	58	24	,	,	PUNCT
flr-74	58	25	correlated	correlate	VERB
flr-74	58	26	errors	error	NOUN
flr-74	58	27	,	,	PUNCT
flr-74	58	28	missing	miss	VERB
flr-74	58	29	values	value	NOUN
flr-74	58	30	,	,	PUNCT
flr-74	58	31	and	and	CCONJ
flr-74	58	32	non	non	ADJ
flr-74	58	33	-	-	ADJ
flr-74	58	34	normal	normal	ADJ
flr-74	58	35	distributions	distribution	NOUN
flr-74	58	36	.	.	PUNCT
flr-74	59	1	artificial	artificial	ADJ
flr-74	59	2	neural	neural	ADJ
flr-74	59	3	network	network	NOUN
flr-74	59	4	analysis	analysis	NOUN
flr-74	59	5	can	can	AUX
flr-74	59	6	not	not	PART
flr-74	59	7	replace	replace	VERB
flr-74	59	8	conventional	conventional	ADJ
flr-74	59	9	statistical	statistical	ADJ
flr-74	59	10	methods	method	NOUN
flr-74	59	11	in	in	ADP
flr-74	59	12	the	the	DET
flr-74	59	13	learning	learn	VERB
flr-74	59	14	sciences	science	NOUN
flr-74	59	15	but	but	CCONJ
flr-74	59	16	may	may	AUX
flr-74	59	17	be	be	AUX
flr-74	59	18	applicable	applicable	ADJ
flr-74	59	19	in	in	ADP
flr-74	59	20	specific	specific	ADJ
flr-74	59	21	cases	case	NOUN
flr-74	59	22	.	.	PUNCT
flr-74	60	1	references	reference	NOUN
flr-74	60	2	aiken	aiken	PROPN
flr-74	60	3	,	,	PUNCT
flr-74	60	4	l.	l.	PROPN
flr-74	60	5	s.	s.	PROPN
flr-74	60	6	,	,	PUNCT
flr-74	60	7	&	&	CCONJ
flr-74	60	8	west	west	PROPN
flr-74	60	9	,	,	PUNCT
flr-74	60	10	s.	s.	PROPN
flr-74	60	11	g.	g.	PROPN
flr-74	60	12	(	(	PUNCT
flr-74	60	13	1991	1991	NUM
flr-74	60	14	)	)	PUNCT
flr-74	60	15	.	.	PUNCT
flr-74	61	1	multiple	multiple	ADJ
flr-74	61	2	regression	regression	NOUN
flr-74	61	3	:	:	PUNCT
flr-74	61	4	testing	testing	NOUN
flr-74	61	5	and	and	CCONJ
flr-74	61	6	interpreting	interpret	VERB
flr-74	61	7	interactions	interaction	NOUN
flr-74	61	8	.	.	PUNCT
flr-74	62	1	newbury	newbury	PROPN
flr-74	62	2	park	park	PROPN
flr-74	62	3	,	,	PUNCT
flr-74	62	4	ca	can	AUX
flr-74	62	5	:	:	PUNCT
flr-74	62	6	sage	sage	VERB
flr-74	62	7	.	.	PUNCT
flr-74	63	1	bates	bate	NOUN
flr-74	63	2	,	,	PUNCT
flr-74	63	3	d.	d.	PROPN
flr-74	63	4	m.	m.	PROPN
flr-74	63	5	,	,	PUNCT
flr-74	63	6	&	&	CCONJ
flr-74	63	7	watts	watts	PROPN
flr-74	63	8	,	,	PUNCT
flr-74	63	9	d.	d.	PROPN
flr-74	63	10	g.	g.	PROPN
flr-74	63	11	(	(	PUNCT
flr-74	63	12	2007	2007	NUM
flr-74	63	13	)	)	PUNCT
flr-74	63	14	.	.	PUNCT
flr-74	64	1	nonlinear	nonlinear	ADJ
flr-74	64	2	regression	regression	NOUN
flr-74	64	3	analysis	analysis	NOUN
flr-74	64	4	and	and	CCONJ
flr-74	64	5	its	its	PRON
flr-74	64	6	applications	application	NOUN
flr-74	64	7	(	(	PUNCT
flr-74	64	8	2nd	2nd	ADJ
flr-74	64	9	ed	ed	NOUN
flr-74	64	10	.	.	PUNCT
flr-74	64	11	)	)	PUNCT
flr-74	64	12	.	.	PUNCT
flr-74	65	1	hoboken	hoboken	PROPN
flr-74	65	2	,	,	PUNCT
flr-74	65	3	nj	nj	PROPN
flr-74	65	4	:	:	PUNCT
flr-74	65	5	wiley	wiley	PROPN
flr-74	65	6	.	.	PUNCT
flr-74	66	1	benitez	benitez	PROPN
flr-74	66	2	,	,	PUNCT
flr-74	66	3	j.	j.	PROPN
flr-74	66	4	m.	m.	PROPN
flr-74	66	5	,	,	PUNCT
flr-74	66	6	castro	castro	PROPN
flr-74	66	7	,	,	PUNCT
flr-74	66	8	j.	j.	PROPN
flr-74	66	9	l.	l.	PROPN
flr-74	66	10	,	,	PUNCT
flr-74	66	11	&	&	CCONJ
flr-74	66	12	requena	requena	PROPN
flr-74	66	13	,	,	PUNCT
flr-74	66	14	i.	i.	NOUN
flr-74	66	15	(	(	PUNCT
flr-74	66	16	1997	1997	NUM
flr-74	66	17	)	)	PUNCT
flr-74	66	18	.	.	PUNCT
flr-74	67	1	are	be	AUX
flr-74	67	2	artificial	artificial	ADJ
flr-74	67	3	neural	neural	ADJ
flr-74	67	4	networks	network	NOUN
flr-74	67	5	black	black	ADJ
flr-74	67	6	boxes	box	NOUN
flr-74	67	7	?	?	PUNCT
flr-74	68	1	ieee	ieee	NOUN
flr-74	68	2	transactions	transaction	NOUN
flr-74	68	3	on	on	ADP
flr-74	68	4	neural	neural	ADJ
flr-74	68	5	networks	network	NOUN
flr-74	68	6	,	,	PUNCT
flr-74	68	7	8	8	NUM
flr-74	68	8	,	,	PUNCT
flr-74	68	9	1156	1156	NUM
flr-74	68	10	-	-	SYM
flr-74	68	11	1164	1164	NUM
flr-74	68	12	.	.	PUNCT
flr-74	69	1	doi:10.1109/72.623216	doi:10.1109/72.623216	VERB
flr-74	69	2	cortez	cortez	PROPN
flr-74	69	3	,	,	PUNCT
flr-74	69	4	p.	p.	PROPN
flr-74	69	5	,	,	PUNCT
flr-74	69	6	&	&	CCONJ
flr-74	69	7	embrechts	embrecht	NOUN
flr-74	69	8	,	,	PUNCT
flr-74	69	9	m.	m.	NOUN
flr-74	69	10	j.	j.	PROPN
flr-74	69	11	(	(	PUNCT
flr-74	69	12	2013	2013	NUM
flr-74	69	13	)	)	PUNCT
flr-74	69	14	.	.	PUNCT
flr-74	70	1	using	use	VERB
flr-74	70	2	sensitivity	sensitivity	NOUN
flr-74	70	3	analysis	analysis	NOUN
flr-74	70	4	and	and	CCONJ
flr-74	70	5	visualization	visualization	NOUN
flr-74	70	6	techniques	technique	NOUN
flr-74	70	7	to	to	PART
flr-74	70	8	open	open	VERB
flr-74	70	9	black	black	ADJ
flr-74	70	10	box	box	PROPN
flr-74	70	11	data	data	NOUN
flr-74	70	12	mining	mining	NOUN
flr-74	70	13	models	model	NOUN
flr-74	70	14	.	.	PUNCT
flr-74	71	1	information	information	NOUN
flr-74	71	2	sciences	sciences	PROPN
flr-74	71	3	,	,	PUNCT
flr-74	71	4	225	225	NUM
flr-74	71	5	,	,	PUNCT
flr-74	71	6	1	1	NUM
flr-74	71	7	-	-	SYM
flr-74	71	8	17	17	NUM
flr-74	71	9	.	.	PUNCT
flr-74	72	1	doi	doi	NOUN
flr-74	72	2	:	:	PUNCT
flr-74	72	3	http://dx.doi.org/10.1016	http://dx.doi.org/10.1016	PROPN
flr-74	72	4	/	/	SYM
flr-74	72	5	j.ins.2012.10.039	j.ins.2012.10.039	NOUN
flr-74	72	6	günther	günther	NOUN
flr-74	72	7	,	,	PUNCT
flr-74	72	8	f.	f.	PROPN
flr-74	72	9	,	,	PUNCT
flr-74	72	10	pigeot	pigeot	PROPN
flr-74	72	11	,	,	PUNCT
flr-74	72	12	i.	i.	PROPN
flr-74	72	13	,	,	PUNCT
flr-74	72	14	&	&	CCONJ
flr-74	72	15	bammann	bammann	PROPN
flr-74	72	16	,	,	PUNCT
flr-74	72	17	k.	k.	PROPN
flr-74	72	18	(	(	PUNCT
flr-74	72	19	2012	2012	NUM
flr-74	72	20	)	)	PUNCT
flr-74	72	21	.	.	PUNCT
flr-74	73	1	artificial	artificial	ADJ
flr-74	73	2	neural	neural	ADJ
flr-74	73	3	networks	network	NOUN
flr-74	73	4	modeling	model	VERB
flr-74	73	5	gene	gene	NOUN
flr-74	73	6	-	-	PUNCT
flr-74	73	7	environment	environment	NOUN
flr-74	73	8	interaction	interaction	NOUN
flr-74	73	9	.	.	PUNCT
flr-74	74	1	bmc	bmc	ADJ
flr-74	74	2	genetics	genetic	NOUN
flr-74	74	3	,	,	PUNCT
flr-74	74	4	13(1	13(1	NUM
flr-74	74	5	)	)	PUNCT
flr-74	74	6	,	,	PUNCT
flr-74	74	7	37	37	NUM
flr-74	74	8	.	.	PUNCT
flr-74	75	1	doi:10.1186/1471	doi:10.1186/1471	NOUN
flr-74	75	2	-	-	PUNCT
flr-74	75	3	2156	2156	NUM
flr-74	75	4	-	-	SYM
flr-74	75	5	13	13	NUM
flr-74	75	6	-	-	SYM
flr-74	75	7	37	37	NUM
flr-74	75	8	hoyle	hoyle	NOUN
flr-74	75	9	,	,	PUNCT
flr-74	75	10	r.	r.	PROPN
flr-74	75	11	h.	h.	PROPN
flr-74	76	1	(	(	PUNCT
flr-74	76	2	ed	ed	NOUN
flr-74	76	3	.	.	PUNCT
flr-74	76	4	)	)	PUNCT
flr-74	76	5	.	.	PUNCT
flr-74	77	1	(	(	PUNCT
flr-74	77	2	2012	2012	NUM
flr-74	77	3	)	)	PUNCT
flr-74	77	4	.	.	PUNCT
flr-74	78	1	handbook	handbook	NOUN
flr-74	78	2	of	of	ADP
flr-74	78	3	structural	structural	ADJ
flr-74	78	4	equation	equation	NOUN
flr-74	78	5	modeling	modeling	NOUN
flr-74	78	6	.	.	PUNCT
flr-74	79	1	new	new	PROPN
flr-74	79	2	york	york	PROPN
flr-74	79	3	:	:	PUNCT
flr-74	79	4	guilford	guilford	PROPN
flr-74	79	5	press	press	PROPN
flr-74	79	6	.	.	PUNCT
flr-74	80	1	intrator	intrator	NOUN
flr-74	80	2	,	,	PUNCT
flr-74	80	3	o.	o.	PROPN
flr-74	80	4	,	,	PUNCT
flr-74	80	5	&	&	CCONJ
flr-74	80	6	intrator	intrator	PROPN
flr-74	80	7	,	,	PUNCT
flr-74	80	8	n.	n.	NOUN
flr-74	80	9	(	(	PUNCT
flr-74	80	10	2001	2001	NUM
flr-74	80	11	)	)	PUNCT
flr-74	80	12	.	.	PUNCT
flr-74	81	1	interpreting	interpret	VERB
flr-74	81	2	neural	neural	ADJ
flr-74	81	3	-	-	PUNCT
flr-74	81	4	network	network	NOUN
flr-74	81	5	results	result	NOUN
flr-74	81	6	:	:	PUNCT
flr-74	81	7	a	a	DET
flr-74	81	8	simulation	simulation	NOUN
flr-74	81	9	study	study	NOUN
flr-74	81	10	.	.	PUNCT
flr-74	82	1	computational	computational	ADJ
flr-74	82	2	statistics	statistic	NOUN
flr-74	82	3	&	&	CCONJ
flr-74	82	4	data	datum	NOUN
flr-74	82	5	analysis	analysis	NOUN
flr-74	82	6	,	,	PUNCT
flr-74	82	7	37	37	NUM
flr-74	82	8	,	,	PUNCT
flr-74	82	9	373	373	NUM
flr-74	82	10	-	-	SYM
flr-74	82	11	393	393	NUM
flr-74	82	12	.	.	PUNCT
flr-74	83	1	doi:10.1016	doi:10.1016	PROPN
flr-74	83	2	/	/	SYM
flr-74	83	3	s0167	s0167	PROPN
flr-74	83	4	-	-	PUNCT
flr-74	83	5	9473(01)00016	9473(01)00016	NUM
flr-74	83	6	-	-	PUNCT
flr-74	83	7	0	0	NUM
flr-74	83	8	kaplan	kaplan	PROPN
flr-74	83	9	,	,	PUNCT
flr-74	83	10	d.	d.	PROPN
flr-74	83	11	(	(	PUNCT
flr-74	83	12	1990	1990	NUM
flr-74	83	13	)	)	PUNCT
flr-74	83	14	.	.	PUNCT
flr-74	84	1	evaluating	evaluate	VERB
flr-74	84	2	and	and	CCONJ
flr-74	84	3	modifying	modify	VERB
flr-74	84	4	covariance	covariance	NOUN
flr-74	84	5	structure	structure	NOUN
flr-74	84	6	models	model	NOUN
flr-74	84	7	:	:	PUNCT
flr-74	84	8	a	a	DET
flr-74	84	9	review	review	NOUN
flr-74	84	10	and	and	CCONJ
flr-74	84	11	recommendation	recommendation	NOUN
flr-74	84	12	.	.	PUNCT
flr-74	85	1	multivariate	multivariate	VERB
flr-74	85	2	behavioral	behavioral	ADJ
flr-74	85	3	research	research	NOUN
flr-74	85	4	,	,	PUNCT
flr-74	85	5	25	25	NUM
flr-74	85	6	,	,	PUNCT
flr-74	85	7	137	137	NUM
flr-74	85	8	-	-	SYM
flr-74	85	9	155	155	NUM
flr-74	85	10	.	.	PUNCT
flr-74	85	11	doi:10.1207	doi:10.1207	PROPN
flr-74	85	12	/	/	SYM
flr-74	85	13	s15327906mbr2502_1	s15327906mbr2502_1	PROPN
flr-74	85	14	luger	luger	NOUN
flr-74	85	15	,	,	PUNCT
flr-74	85	16	g.	g.	PROPN
flr-74	85	17	f.	f.	PROPN
flr-74	85	18	(	(	PUNCT
flr-74	85	19	2009	2009	NUM
flr-74	85	20	)	)	PUNCT
flr-74	85	21	.	.	PUNCT
flr-74	86	1	artificial	artificial	ADJ
flr-74	86	2	intelligence	intelligence	NOUN
flr-74	86	3	:	:	PUNCT
flr-74	86	4	structures	structure	NOUN
flr-74	86	5	and	and	CCONJ
flr-74	86	6	strategies	strategy	NOUN
flr-74	86	7	for	for	ADP
flr-74	86	8	complex	complex	ADJ
flr-74	86	9	problem	problem	NOUN
flr-74	86	10	solving	solve	VERB
flr-74	86	11	(	(	PUNCT
flr-74	86	12	6th	6th	ADJ
flr-74	86	13	ed	ed	NOUN
flr-74	86	14	.	.	PUNCT
flr-74	86	15	)	)	PUNCT
flr-74	86	16	.	.	PUNCT
flr-74	87	1	boston	boston	PROPN
flr-74	87	2	,	,	PUNCT
flr-74	87	3	ma	ma	PROPN
flr-74	87	4	:	:	PUNCT
flr-74	87	5	pearson	pearson	PROPN
flr-74	87	6	education	education	PROPN
flr-74	87	7	.	.	PUNCT
flr-74	88	1	musso	musso	PROPN
flr-74	88	2	,	,	PUNCT
flr-74	88	3	m.	m.	PROPN
flr-74	88	4	f.	f.	PROPN
flr-74	88	5	,	,	PUNCT
flr-74	88	6	kyndt	kyndt	PROPN
flr-74	88	7	,	,	PUNCT
flr-74	88	8	e.	e.	PROPN
flr-74	88	9	,	,	PUNCT
flr-74	88	10	cascallar	cascallar	PROPN
flr-74	88	11	,	,	PUNCT
flr-74	88	12	e.	e.	PROPN
flr-74	88	13	c.	c.	PROPN
flr-74	88	14	,	,	PUNCT
flr-74	88	15	&	&	CCONJ
flr-74	88	16	dochy	dochy	PROPN
flr-74	88	17	,	,	PUNCT
flr-74	88	18	f.	f.	PROPN
flr-74	88	19	(	(	PUNCT
flr-74	88	20	2013	2013	NUM
flr-74	88	21	)	)	PUNCT
flr-74	88	22	.	.	PUNCT
flr-74	89	1	predicting	predict	VERB
flr-74	89	2	general	general	ADJ
flr-74	89	3	academic	academic	ADJ
flr-74	89	4	performance	performance	NOUN
flr-74	89	5	and	and	CCONJ
flr-74	89	6	identifying	identify	VERB
flr-74	89	7	the	the	DET
flr-74	89	8	differential	differential	ADJ
flr-74	89	9	contribution	contribution	NOUN
flr-74	89	10	of	of	ADP
flr-74	89	11	participating	participate	VERB
flr-74	89	12	variables	variable	NOUN
flr-74	89	13	using	use	VERB
flr-74	89	14	artificial	artificial	ADJ
flr-74	89	15	neural	neural	ADJ
flr-74	89	16	networks	network	NOUN
flr-74	89	17	.	.	PUNCT
flr-74	90	1	frontline	frontline	NOUN
flr-74	90	2	learning	learn	VERB
flr-74	90	3	research	research	NOUN
flr-74	90	4	,	,	PUNCT
flr-74	90	5	1	1	NUM
flr-74	90	6	,	,	PUNCT
flr-74	90	7	42	42	NUM
flr-74	90	8	-	-	SYM
flr-74	90	9	71	71	NUM
flr-74	90	10	.	.	PUNCT
flr-74	91	1	retrieved	retrieve	VERB
flr-74	91	2	from	from	ADP
flr-74	91	3	http://journals.sfu.ca/flr/index.php/journal/article/view/13	http://journals.sfu.ca/flr/index.php/journal/article/view/13	ADJ
flr-74	91	4	p.	p.	NOUN
flr-74	91	5	edelsbrunner	edelsbrunner	NOUN
flr-74	91	6	and	and	CCONJ
flr-74	91	7	m.	m.	NOUN
flr-74	91	8	schneider	schneider	PROPN
flr-74	92	1	102	102	NUM
flr-74	93	1	|	|	ADV
flr-74	93	2	f	f	NOUN
flr-74	93	3	l	l	NOUN
flr-74	93	4	r	r	NOUN
flr-74	93	5	scarborough	scarborough	PROPN
flr-74	93	6	,	,	PUNCT
flr-74	93	7	d.	d.	PROPN
flr-74	93	8	,	,	PUNCT
flr-74	93	9	&	&	CCONJ
flr-74	93	10	somers	somers	PROPN
flr-74	93	11	,	,	PUNCT
flr-74	93	12	m.	m.	NOUN
flr-74	93	13	j.	j.	PROPN
flr-74	93	14	(	(	PUNCT
flr-74	93	15	2006	2006	NUM
flr-74	93	16	)	)	PUNCT
flr-74	93	17	.	.	PUNCT
flr-74	94	1	neural	neural	ADJ
flr-74	94	2	networks	network	NOUN
flr-74	94	3	in	in	ADP
flr-74	94	4	organizational	organizational	ADJ
flr-74	94	5	research	research	NOUN
flr-74	94	6	:	:	PUNCT
flr-74	94	7	applying	apply	VERB
flr-74	94	8	pattern	pattern	NOUN
flr-74	94	9	recognition	recognition	NOUN
flr-74	94	10	to	to	ADP
flr-74	94	11	the	the	DET
flr-74	94	12	analysis	analysis	NOUN
flr-74	94	13	of	of	ADP
flr-74	94	14	organizational	organizational	ADJ
flr-74	94	15	behavior	behavior	NOUN
flr-74	94	16	(	(	PUNCT
flr-74	94	17	pp	pp	ADJ
flr-74	94	18	.	.	PUNCT
flr-74	95	1	137	137	NUM
flr-74	95	2	-	-	SYM
flr-74	95	3	144	144	NUM
flr-74	95	4	)	)	PUNCT
flr-74	95	5	.	.	PUNCT
flr-74	96	1	washington	washington	PROPN
flr-74	96	2	,	,	PUNCT
flr-74	96	3	dc	dc	PROPN
flr-74	96	4	:	:	PUNCT
flr-74	96	5	american	american	PROPN
flr-74	96	6	psychological	psychological	PROPN
flr-74	96	7	association	association	PROPN
flr-74	96	8	.	.	PUNCT
flr-74	97	1	song	song	PROPN
flr-74	97	2	,	,	PUNCT
flr-74	97	3	x.	x.	PROPN
flr-74	97	4	y.	y.	PROPN
flr-74	97	5	,	,	PUNCT
flr-74	97	6	&	&	CCONJ
flr-74	97	7	lee	lee	PROPN
flr-74	97	8	,	,	PUNCT
flr-74	97	9	s.	s.	PROPN
flr-74	97	10	y.	y.	PROPN
flr-74	97	11	(	(	PUNCT
flr-74	97	12	2012	2012	NUM
flr-74	97	13	)	)	PUNCT
flr-74	97	14	.	.	PUNCT
flr-74	98	1	basic	basic	ADJ
flr-74	98	2	and	and	CCONJ
flr-74	98	3	advanced	advanced	ADJ
flr-74	98	4	bayesian	bayesian	NOUN
flr-74	98	5	structural	structural	ADJ
flr-74	98	6	equation	equation	NOUN
flr-74	98	7	modeling	modeling	NOUN
flr-74	98	8	:	:	PUNCT
flr-74	98	9	with	with	ADP
flr-74	98	10	applications	application	NOUN
flr-74	98	11	in	in	ADP
flr-74	98	12	the	the	DET
flr-74	98	13	medical	medical	ADJ
flr-74	98	14	and	and	CCONJ
flr-74	98	15	behavioral	behavioral	ADJ
flr-74	98	16	sciences	science	NOUN
flr-74	98	17	.	.	PUNCT
flr-74	99	1	chichester	chichester	PROPN
flr-74	99	2	,	,	PUNCT
flr-74	99	3	uk	uk	PROPN
flr-74	99	4	:	:	PUNCT
flr-74	99	5	john	john	PROPN
flr-74	99	6	wiley	wiley	PROPN
flr-74	99	7	&	&	CCONJ
flr-74	99	8	sons	son	NOUN
flr-74	99	9	.	.	PUNCT