id	sid	tid	token	lemma	pos
fcis-11957	1	1	frontiers	frontier	NOUN
fcis-11957	1	2	in	in	ADP
fcis-11957	1	3	computing	computing	NOUN
fcis-11957	1	4	and	and	CCONJ
fcis-11957	1	5	intelligent	intelligent	ADJ
fcis-11957	1	6	systems	system	NOUN
fcis-11957	1	7	issn	issn	VERB
fcis-11957	1	8	:	:	PUNCT
fcis-11957	1	9	2832	2832	NUM
fcis-11957	1	10	-	-	SYM
fcis-11957	1	11	6024	6024	NUM
fcis-11957	1	12	|	|	NOUN
fcis-11957	1	13	vol	vol	NOUN
fcis-11957	1	14	.	.	PROPN
fcis-11957	2	1	5	5	NUM
fcis-11957	2	2	,	,	PUNCT
fcis-11957	2	3	no	no	INTJ
fcis-11957	2	4	.	.	NOUN
fcis-11957	2	5	1	1	NUM
fcis-11957	2	6	,	,	PUNCT
fcis-11957	2	7	2023	2023	NUM
fcis-11957	2	8	100	100	NUM
fcis-11957	2	9	application	application	NOUN
fcis-11957	2	10	and	and	CCONJ
fcis-11957	2	11	research	research	NOUN
fcis-11957	2	12	based	base	VERB
fcis-11957	2	13	on	on	ADP
fcis-11957	2	14	anova	anova	PROPN
fcis-11957	2	15	and	and	CCONJ
fcis-11957	2	16	logistic	logistic	ADJ
fcis-11957	2	17	regression	regression	NOUN
fcis-11957	2	18	models	model	NOUN
fcis-11957	2	19	guowei	guowei	PROPN
fcis-11957	2	20	li	li	PROPN
fcis-11957	2	21	,	,	PUNCT
fcis-11957	2	22	shanwei	shanwei	PROPN
fcis-11957	2	23	yang	yang	PROPN
fcis-11957	2	24	,	,	PUNCT
fcis-11957	2	25	sai	sai	PROPN
fcis-11957	2	26	li	li	PROPN
fcis-11957	2	27	,	,	PUNCT
fcis-11957	2	28	jie	jie	PROPN
fcis-11957	2	29	jian	jian	PROPN
fcis-11957	2	30	,	,	PUNCT
fcis-11957	2	31	juan	juan	PROPN
fcis-11957	2	32	li	li	PROPN
fcis-11957	3	1	*	*	PROPN
fcis-11957	3	2	school	school	PROPN
fcis-11957	3	3	of	of	ADP
fcis-11957	3	4	information	information	NOUN
fcis-11957	3	5	engineering	engineering	NOUN
fcis-11957	3	6	,	,	PUNCT
fcis-11957	3	7	wuhan	wuhan	PROPN
fcis-11957	3	8	business	business	PROPN
fcis-11957	3	9	university	university	PROPN
fcis-11957	3	10	,	,	PUNCT
fcis-11957	3	11	wuhan	wuhan	PROPN
fcis-11957	3	12	430056	430056	NUM
fcis-11957	3	13	,	,	PUNCT
fcis-11957	3	14	china	china	PROPN
fcis-11957	3	15	*	*	PUNCT
fcis-11957	3	16	corresponding	correspond	VERB
fcis-11957	3	17	author	author	NOUN
fcis-11957	3	18	:	:	PUNCT
fcis-11957	3	19	juan	juan	PROPN
fcis-11957	3	20	li	li	PROPN
fcis-11957	3	21	(	(	PUNCT
fcis-11957	3	22	email	email	NOUN
fcis-11957	3	23	:	:	PUNCT
fcis-11957	3	24	looj@wbu.edu.cn	looj@wbu.edu.cn	PROPN
fcis-11957	3	25	)	)	PUNCT
fcis-11957	3	26	abstract	abstract	NOUN
fcis-11957	3	27	:	:	PUNCT
fcis-11957	3	28	the	the	DET
fcis-11957	3	29	silk	silk	NOUN
fcis-11957	3	30	road	road	NOUN
fcis-11957	3	31	was	be	AUX
fcis-11957	3	32	a	a	DET
fcis-11957	3	33	passage	passage	NOUN
fcis-11957	3	34	for	for	ADP
fcis-11957	3	35	cultural	cultural	ADJ
fcis-11957	3	36	exchanges	exchange	NOUN
fcis-11957	3	37	between	between	ADP
fcis-11957	3	38	china	china	PROPN
fcis-11957	3	39	and	and	CCONJ
fcis-11957	3	40	the	the	DET
fcis-11957	3	41	west	west	NOUN
fcis-11957	3	42	in	in	ADP
fcis-11957	3	43	ancient	ancient	ADJ
fcis-11957	3	44	times	time	NOUN
fcis-11957	3	45	,	,	PUNCT
fcis-11957	3	46	of	of	ADP
fcis-11957	3	47	which	which	DET
fcis-11957	3	48	glass	glass	NOUN
fcis-11957	3	49	was	be	AUX
fcis-11957	3	50	valuable	valuable	ADJ
fcis-11957	3	51	material	material	ADJ
fcis-11957	3	52	evidence	evidence	NOUN
fcis-11957	3	53	of	of	ADP
fcis-11957	3	54	early	early	ADJ
fcis-11957	3	55	trade	trade	NOUN
fcis-11957	3	56	exchanges	exchange	NOUN
fcis-11957	3	57	,	,	PUNCT
fcis-11957	3	58	and	and	CCONJ
fcis-11957	3	59	china	china	PROPN
fcis-11957	3	60	's	's	PART
fcis-11957	3	61	early	early	ADJ
fcis-11957	3	62	glass	glass	NOUN
fcis-11957	3	63	also	also	ADV
fcis-11957	3	64	led	lead	VERB
fcis-11957	3	65	to	to	ADP
fcis-11957	3	66	different	different	ADJ
fcis-11957	3	67	chemical	chemical	NOUN
fcis-11957	3	68	compositions	composition	NOUN
fcis-11957	3	69	after	after	ADP
fcis-11957	3	70	absorbing	absorb	VERB
fcis-11957	3	71	some	some	DET
fcis-11957	3	72	foreign	foreign	ADJ
fcis-11957	3	73	technologies	technology	NOUN
fcis-11957	3	74	.	.	PUNCT
fcis-11957	4	1	for	for	ADP
fcis-11957	4	2	example	example	NOUN
fcis-11957	4	3	,	,	PUNCT
fcis-11957	4	4	nowadays	nowadays	ADV
fcis-11957	4	5	,	,	PUNCT
fcis-11957	4	6	most	most	ADJ
fcis-11957	4	7	glass	glass	NOUN
fcis-11957	4	8	cultural	cultural	ADJ
fcis-11957	4	9	relics	relic	NOUN
fcis-11957	4	10	are	be	AUX
fcis-11957	4	11	divided	divide	VERB
fcis-11957	4	12	into	into	ADP
fcis-11957	4	13	two	two	NUM
fcis-11957	4	14	categories	category	NOUN
fcis-11957	4	15	,	,	PUNCT
fcis-11957	4	16	and	and	CCONJ
fcis-11957	4	17	the	the	DET
fcis-11957	4	18	identification	identification	NOUN
fcis-11957	4	19	,	,	PUNCT
fcis-11957	4	20	analysis	analysis	NOUN
fcis-11957	4	21	and	and	CCONJ
fcis-11957	4	22	classification	classification	NOUN
fcis-11957	4	23	of	of	ADP
fcis-11957	4	24	them	they	PRON
fcis-11957	4	25	and	and	CCONJ
fcis-11957	4	26	similar	similar	ADJ
fcis-11957	4	27	problems	problem	NOUN
fcis-11957	4	28	are	be	AUX
fcis-11957	4	29	also	also	ADV
fcis-11957	4	30	the	the	DET
fcis-11957	4	31	direction	direction	NOUN
fcis-11957	4	32	that	that	PRON
fcis-11957	4	33	needs	need	VERB
fcis-11957	4	34	to	to	PART
fcis-11957	4	35	be	be	AUX
fcis-11957	4	36	studied	study	VERB
fcis-11957	4	37	.	.	PUNCT
fcis-11957	5	1	in	in	ADP
fcis-11957	5	2	view	view	NOUN
fcis-11957	5	3	of	of	ADP
fcis-11957	5	4	such	such	ADJ
fcis-11957	5	5	problems	problem	NOUN
fcis-11957	5	6	,	,	PUNCT
fcis-11957	5	7	we	we	PRON
fcis-11957	5	8	propose	propose	VERB
fcis-11957	5	9	to	to	PART
fcis-11957	5	10	solve	solve	VERB
fcis-11957	5	11	such	such	ADJ
fcis-11957	5	12	problems	problem	NOUN
fcis-11957	5	13	by	by	ADP
fcis-11957	5	14	studying	study	VERB
fcis-11957	5	15	one	one	NUM
fcis-11957	5	16	-	-	PUNCT
fcis-11957	5	17	way	way	NOUN
fcis-11957	5	18	anova	anova	PROPN
fcis-11957	5	19	and	and	CCONJ
fcis-11957	5	20	binary	binary	ADJ
fcis-11957	5	21	classification	classification	NOUN
fcis-11957	5	22	logistic	logistic	ADJ
fcis-11957	5	23	regression	regression	NOUN
fcis-11957	5	24	model	model	NOUN
fcis-11957	5	25	algorithm	algorithm	NOUN
fcis-11957	5	26	,	,	PUNCT
fcis-11957	5	27	in	in	ADP
fcis-11957	5	28	which	which	PRON
fcis-11957	5	29	one	one	NUM
fcis-11957	5	30	-	-	PUNCT
fcis-11957	5	31	way	way	NOUN
fcis-11957	5	32	anova	anova	PROPN
fcis-11957	5	33	is	be	AUX
fcis-11957	5	34	a	a	DET
fcis-11957	5	35	significant	significant	ADJ
fcis-11957	5	36	test	test	NOUN
fcis-11957	5	37	of	of	ADP
fcis-11957	5	38	the	the	DET
fcis-11957	5	39	mean	mean	ADJ
fcis-11957	5	40	difference	difference	NOUN
fcis-11957	5	41	between	between	ADP
fcis-11957	5	42	two	two	NUM
fcis-11957	5	43	or	or	CCONJ
fcis-11957	5	44	more	more	ADJ
fcis-11957	5	45	samples	sample	NOUN
fcis-11957	5	46	(	(	PUNCT
fcis-11957	5	47	i.e.	i.e.	X
fcis-11957	5	48	factors	factor	NOUN
fcis-11957	5	49	)	)	PUNCT
fcis-11957	5	50	,	,	PUNCT
fcis-11957	5	51	that	that	ADV
fcis-11957	5	52	is	is	ADV
fcis-11957	5	53	,	,	PUNCT
fcis-11957	5	54	it	it	PRON
fcis-11957	5	55	performs	perform	VERB
fcis-11957	5	56	certain	certain	ADJ
fcis-11957	5	57	screening	screening	NOUN
fcis-11957	5	58	and	and	CCONJ
fcis-11957	5	59	testing	testing	NOUN
fcis-11957	5	60	on	on	ADP
fcis-11957	5	61	the	the	DET
fcis-11957	5	62	relevant	relevant	ADJ
fcis-11957	5	63	data	datum	NOUN
fcis-11957	5	64	of	of	ADP
fcis-11957	5	65	the	the	DET
fcis-11957	5	66	required	require	VERB
fcis-11957	5	67	classification	classification	NOUN
fcis-11957	5	68	identification	identification	NOUN
fcis-11957	5	69	,	,	PUNCT
fcis-11957	5	70	and	and	CCONJ
fcis-11957	5	71	then	then	ADV
fcis-11957	5	72	completes	complete	VERB
fcis-11957	5	73	the	the	DET
fcis-11957	5	74	classification	classification	NOUN
fcis-11957	5	75	and	and	CCONJ
fcis-11957	5	76	identification	identification	NOUN
fcis-11957	5	77	of	of	ADP
fcis-11957	5	78	the	the	DET
fcis-11957	5	79	results	result	NOUN
fcis-11957	5	80	of	of	ADP
fcis-11957	5	81	the	the	DET
fcis-11957	5	82	screening	screening	NOUN
fcis-11957	5	83	test	test	NOUN
fcis-11957	5	84	by	by	ADP
fcis-11957	5	85	the	the	DET
fcis-11957	5	86	0	0	NUM
fcis-11957	5	87	-	-	SYM
fcis-11957	5	88	1	1	NUM
fcis-11957	5	89	variable	variable	NOUN
fcis-11957	5	90	and	and	CCONJ
fcis-11957	5	91	the	the	DET
fcis-11957	5	92	dependent	dependent	ADJ
fcis-11957	5	93	variable	variable	NOUN
fcis-11957	5	94	of	of	ADP
fcis-11957	5	95	the	the	DET
fcis-11957	5	96	two	two	NUM
fcis-11957	5	97	-	-	PUNCT
fcis-11957	5	98	way	way	NOUN
fcis-11957	5	99	logistic	logistic	ADJ
fcis-11957	5	100	regression	regression	NOUN
fcis-11957	5	101	model	model	NOUN
fcis-11957	5	102	.	.	PUNCT
fcis-11957	6	1	the	the	DET
fcis-11957	6	2	test	test	NOUN
fcis-11957	6	3	of	of	ADP
fcis-11957	6	4	the	the	DET
fcis-11957	6	5	result	result	NOUN
fcis-11957	6	6	prediction	prediction	NOUN
fcis-11957	6	7	by	by	ADP
fcis-11957	6	8	extracting	extract	VERB
fcis-11957	6	9	the	the	DET
fcis-11957	6	10	differential	differential	ADJ
fcis-11957	6	11	data	datum	NOUN
fcis-11957	6	12	obtained	obtain	VERB
fcis-11957	6	13	by	by	ADP
fcis-11957	6	14	the	the	DET
fcis-11957	6	15	former	former	NOUN
fcis-11957	6	16	,	,	PUNCT
fcis-11957	6	17	that	that	ADV
fcis-11957	6	18	is	is	ADV
fcis-11957	6	19	,	,	PUNCT
fcis-11957	6	20	its	its	PRON
fcis-11957	6	21	sensitivity	sensitivity	NOUN
fcis-11957	6	22	analysis	analysis	NOUN
fcis-11957	6	23	,	,	PUNCT
fcis-11957	6	24	can	can	AUX
fcis-11957	6	25	confirm	confirm	VERB
fcis-11957	6	26	the	the	DET
fcis-11957	6	27	accuracy	accuracy	NOUN
fcis-11957	6	28	and	and	CCONJ
fcis-11957	6	29	effectiveness	effectiveness	NOUN
fcis-11957	6	30	of	of	ADP
fcis-11957	6	31	the	the	DET
fcis-11957	6	32	two	two	NUM
fcis-11957	6	33	model	model	NOUN
fcis-11957	6	34	algorithms	algorithm	NOUN
fcis-11957	6	35	in	in	ADP
fcis-11957	6	36	this	this	DET
fcis-11957	6	37	regard	regard	NOUN
fcis-11957	6	38	.	.	PUNCT
fcis-11957	7	1	keywords	keyword	NOUN
fcis-11957	7	2	:	:	PUNCT
fcis-11957	7	3	0ne	0ne	ADJ
fcis-11957	7	4	-	-	PUNCT
fcis-11957	7	5	way	way	NOUN
fcis-11957	7	6	anova	anova	X
fcis-11957	7	7	;	;	PUNCT
fcis-11957	7	8	dichotomous	dichotomous	ADJ
fcis-11957	7	9	logistic	logistic	ADJ
fcis-11957	7	10	regression	regression	NOUN
fcis-11957	7	11	;	;	PUNCT
fcis-11957	7	12	sensitivity	sensitivity	NOUN
fcis-11957	7	13	analysis	analysis	NOUN
fcis-11957	7	14	.	.	PUNCT
fcis-11957	8	1	1	1	X
fcis-11957	8	2	.	.	X
fcis-11957	8	3	introduction	introduction	NOUN
fcis-11957	8	4	at	at	ADP
fcis-11957	8	5	present	present	ADJ
fcis-11957	8	6	,	,	PUNCT
fcis-11957	8	7	with	with	ADP
fcis-11957	8	8	the	the	DET
fcis-11957	8	9	archaeological	archaeological	ADJ
fcis-11957	8	10	research	research	NOUN
fcis-11957	8	11	and	and	CCONJ
fcis-11957	8	12	discovery	discovery	NOUN
fcis-11957	8	13	of	of	ADP
fcis-11957	8	14	cultural	cultural	ADJ
fcis-11957	8	15	relics	relic	NOUN
fcis-11957	8	16	in	in	ADP
fcis-11957	8	17	china	china	PROPN
fcis-11957	8	18	,	,	PUNCT
fcis-11957	8	19	a	a	DET
fcis-11957	8	20	large	large	ADJ
fcis-11957	8	21	number	number	NOUN
fcis-11957	8	22	of	of	ADP
fcis-11957	8	23	archaeological	archaeological	ADJ
fcis-11957	8	24	research	research	NOUN
fcis-11957	8	25	experts	expert	NOUN
fcis-11957	8	26	have	have	AUX
fcis-11957	8	27	joined	join	VERB
fcis-11957	8	28	in	in	ADP
fcis-11957	8	29	,	,	PUNCT
fcis-11957	8	30	and	and	CCONJ
fcis-11957	8	31	among	among	ADP
fcis-11957	8	32	them	they	PRON
fcis-11957	8	33	,	,	PUNCT
fcis-11957	8	34	the	the	DET
fcis-11957	8	35	identification	identification	NOUN
fcis-11957	8	36	and	and	CCONJ
fcis-11957	8	37	historical	historical	ADJ
fcis-11957	8	38	cognition	cognition	NOUN
fcis-11957	8	39	and	and	CCONJ
fcis-11957	8	40	analysis	analysis	NOUN
fcis-11957	8	41	of	of	ADP
fcis-11957	8	42	a	a	DET
fcis-11957	8	43	large	large	ADJ
fcis-11957	8	44	number	number	NOUN
fcis-11957	8	45	of	of	ADP
fcis-11957	8	46	cultural	cultural	ADJ
fcis-11957	8	47	relics	relic	NOUN
fcis-11957	8	48	after	after	SCONJ
fcis-11957	8	49	their	their	PRON
fcis-11957	8	50	discovery	discovery	NOUN
fcis-11957	8	51	is	be	AUX
fcis-11957	8	52	the	the	DET
fcis-11957	8	53	focus	focus	NOUN
fcis-11957	8	54	and	and	CCONJ
fcis-11957	8	55	difficulty	difficulty	NOUN
fcis-11957	8	56	of	of	ADP
fcis-11957	8	57	the	the	DET
fcis-11957	8	58	work	work	NOUN
fcis-11957	8	59	afterwards	afterwards	ADV
fcis-11957	8	60	,	,	PUNCT
fcis-11957	8	61	and	and	CCONJ
fcis-11957	8	62	in	in	ADP
fcis-11957	8	63	the	the	DET
fcis-11957	8	64	process	process	NOUN
fcis-11957	8	65	of	of	ADP
fcis-11957	8	66	identifying	identify	VERB
fcis-11957	8	67	cultural	cultural	ADJ
fcis-11957	8	68	relics	relic	NOUN
fcis-11957	8	69	and	and	CCONJ
fcis-11957	8	70	types	type	NOUN
fcis-11957	8	71	and	and	CCONJ
fcis-11957	8	72	components	component	NOUN
fcis-11957	8	73	,	,	PUNCT
fcis-11957	8	74	a	a	DET
fcis-11957	8	75	large	large	ADJ
fcis-11957	8	76	set	set	NOUN
fcis-11957	8	77	of	of	ADP
fcis-11957	8	78	influencing	influence	VERB
fcis-11957	8	79	factors	factor	NOUN
fcis-11957	8	80	and	and	CCONJ
fcis-11957	8	81	experimental	experimental	ADJ
fcis-11957	8	82	controls	control	NOUN
fcis-11957	8	83	and	and	CCONJ
fcis-11957	8	84	natural	natural	ADJ
fcis-11957	8	85	influences	influence	NOUN
fcis-11957	8	86	lead	lead	VERB
fcis-11957	8	87	to	to	PART
fcis-11957	8	88	hindrance	hindrance	VERB
fcis-11957	8	89	also	also	ADV
fcis-11957	8	90	make	make	VERB
fcis-11957	8	91	the	the	DET
fcis-11957	8	92	process	process	NOUN
fcis-11957	8	93	more	more	ADV
fcis-11957	8	94	tedious	tedious	ADJ
fcis-11957	8	95	.	.	PUNCT
fcis-11957	9	1	one	one	NUM
fcis-11957	9	2	-	-	PUNCT
fcis-11957	9	3	factor	factor	NOUN
fcis-11957	9	4	anova	anova	PROPN
fcis-11957	9	5	is	be	AUX
fcis-11957	9	6	a	a	DET
fcis-11957	9	7	statistical	statistical	ADJ
fcis-11957	9	8	test	test	NOUN
fcis-11957	9	9	that	that	PRON
fcis-11957	9	10	compares	compare	VERB
fcis-11957	9	11	the	the	DET
fcis-11957	9	12	difference	difference	NOUN
fcis-11957	9	13	between	between	ADP
fcis-11957	9	14	the	the	DET
fcis-11957	9	15	means	mean	NOUN
fcis-11957	9	16	of	of	ADP
fcis-11957	9	17	groups	group	NOUN
fcis-11957	9	18	in	in	ADP
fcis-11957	9	19	a	a	DET
fcis-11957	9	20	sample	sample	NOUN
fcis-11957	9	21	when	when	SCONJ
fcis-11957	9	22	only	only	ADV
fcis-11957	9	23	one	one	NUM
fcis-11957	9	24	independent	independent	ADJ
fcis-11957	9	25	variable	variable	NOUN
fcis-11957	9	26	or	or	CCONJ
fcis-11957	9	27	factor	factor	NOUN
fcis-11957	9	28	is	be	AUX
fcis-11957	9	29	considered	consider	VERB
fcis-11957	9	30	.	.	PUNCT
fcis-11957	10	1	based	base	VERB
fcis-11957	10	2	on	on	ADP
fcis-11957	10	3	this	this	PRON
fcis-11957	10	4	,	,	PUNCT
fcis-11957	10	5	ni	ni	PROPN
fcis-11957	10	6	feng	feng	PROPN
fcis-11957	10	7	makes	make	VERB
fcis-11957	10	8	it	it	PRON
fcis-11957	10	9	widely	widely	ADV
fcis-11957	10	10	used	use	VERB
fcis-11957	10	11	in	in	ADP
fcis-11957	10	12	the	the	DET
fcis-11957	10	13	homogeneity	homogeneity	NOUN
fcis-11957	10	14	test	test	NOUN
fcis-11957	10	15	of	of	ADP
fcis-11957	10	16	samples	sample	NOUN
fcis-11957	10	17	by	by	ADP
fcis-11957	10	18	explaining	explain	VERB
fcis-11957	10	19	the	the	DET
fcis-11957	10	20	principle	principle	ADJ
fcis-11957	10	21	and	and	CCONJ
fcis-11957	10	22	calculation	calculation	NOUN
fcis-11957	10	23	steps	step	NOUN
fcis-11957	10	24	of	of	ADP
fcis-11957	10	25	factor	factor	NOUN
fcis-11957	10	26	anova	anova	PROPN
fcis-11957	10	27	and	and	CCONJ
fcis-11957	10	28	combining	combine	VERB
fcis-11957	10	29	it	it	PRON
fcis-11957	10	30	with	with	ADP
fcis-11957	10	31	practical	practical	ADJ
fcis-11957	10	32	,	,	PUNCT
fcis-11957	10	33	shallow	shallow	ADJ
fcis-11957	10	34	analysis	analysis	NOUN
fcis-11957	10	35	of	of	ADP
fcis-11957	10	36	one	one	NUM
fcis-11957	10	37	-	-	PUNCT
fcis-11957	10	38	factor	factor	NOUN
fcis-11957	10	39	anova	anova	PROPN
fcis-11957	10	40	in	in	ADP
fcis-11957	10	41	the	the	DET
fcis-11957	10	42	homogeneity	homogeneity	NOUN
fcis-11957	10	43	test	test	NOUN
fcis-11957	10	44	of	of	ADP
fcis-11957	10	45	coal	coal	NOUN
fcis-11957	10	46	samples	sample	NOUN
fcis-11957	10	47	.	.	PUNCT
fcis-11957	11	1	binary	binary	ADJ
fcis-11957	11	2	logistic	logistic	PROPN
fcis-11957	11	3	regression	regression	NOUN
fcis-11957	11	4	model	model	NOUN
fcis-11957	11	5	is	be	AUX
fcis-11957	11	6	also	also	ADV
fcis-11957	11	7	one	one	NUM
fcis-11957	11	8	of	of	ADP
fcis-11957	11	9	the	the	DET
fcis-11957	11	10	most	most	ADV
fcis-11957	11	11	classical	classical	ADJ
fcis-11957	11	12	methods	method	NOUN
fcis-11957	11	13	of	of	ADP
fcis-11957	11	14	machine	machine	NOUN
fcis-11957	11	15	learning	learning	NOUN
fcis-11957	11	16	.	.	PUNCT
fcis-11957	12	1	based	base	VERB
fcis-11957	12	2	on	on	ADP
fcis-11957	12	3	this	this	PRON
fcis-11957	12	4	,	,	PUNCT
fcis-11957	12	5	wu	wu	PROPN
fcis-11957	12	6	jiao	jiao	PROPN
fcis-11957	12	7	established	establish	VERB
fcis-11957	12	8	a	a	DET
fcis-11957	12	9	binary	binary	ADJ
fcis-11957	12	10	logistic	logistic	ADJ
fcis-11957	12	11	regression	regression	NOUN
fcis-11957	12	12	model	model	NOUN
fcis-11957	12	13	for	for	ADP
fcis-11957	12	14	studying	study	VERB
fcis-11957	12	15	the	the	DET
fcis-11957	12	16	factors	factor	NOUN
fcis-11957	12	17	influencing	influence	VERB
fcis-11957	12	18	the	the	DET
fcis-11957	12	19	nutritional	nutritional	ADJ
fcis-11957	12	20	status	status	NOUN
fcis-11957	12	21	of	of	ADP
fcis-11957	12	22	children	child	NOUN
fcis-11957	12	23	aged	age	VERB
fcis-11957	12	24	1	1	NUM
fcis-11957	12	25	to	to	PART
fcis-11957	12	26	3	3	NUM
fcis-11957	12	27	years	year	NOUN
fcis-11957	12	28	old	old	ADJ
fcis-11957	12	29	,	,	PUNCT
fcis-11957	12	30	which	which	PRON
fcis-11957	12	31	enables	enable	VERB
fcis-11957	12	32	him	he	PRON
fcis-11957	12	33	to	to	PART
fcis-11957	12	34	take	take	VERB
fcis-11957	12	35	appropriate	appropriate	ADJ
fcis-11957	12	36	intervention	intervention	NOUN
fcis-11957	12	37	strategies	strategy	NOUN
fcis-11957	12	38	in	in	ADP
fcis-11957	12	39	advance	advance	NOUN
fcis-11957	12	40	to	to	PART
fcis-11957	12	41	prevent	prevent	VERB
fcis-11957	12	42	malnutrition	malnutrition	NOUN
fcis-11957	12	43	in	in	ADP
fcis-11957	12	44	children	child	NOUN
fcis-11957	12	45	and	and	CCONJ
fcis-11957	12	46	improve	improve	VERB
fcis-11957	12	47	their	their	PRON
fcis-11957	12	48	nutritional	nutritional	ADJ
fcis-11957	12	49	status	status	NOUN
fcis-11957	12	50	.	.	PUNCT
fcis-11957	13	1	based	base	VERB
fcis-11957	13	2	on	on	ADP
fcis-11957	13	3	the	the	DET
fcis-11957	13	4	extensive	extensive	ADJ
fcis-11957	13	5	research	research	NOUN
fcis-11957	13	6	and	and	CCONJ
fcis-11957	13	7	application	application	NOUN
fcis-11957	13	8	of	of	ADP
fcis-11957	13	9	these	these	DET
fcis-11957	13	10	models	model	NOUN
fcis-11957	13	11	and	and	CCONJ
fcis-11957	13	12	algorithms	algorithm	NOUN
fcis-11957	13	13	in	in	ADP
fcis-11957	13	14	recent	recent	ADJ
fcis-11957	13	15	years	year	NOUN
fcis-11957	13	16	,	,	PUNCT
fcis-11957	13	17	we	we	PRON
fcis-11957	13	18	intend	intend	VERB
fcis-11957	13	19	to	to	PART
fcis-11957	13	20	use	use	VERB
fcis-11957	13	21	these	these	DET
fcis-11957	13	22	models	model	NOUN
fcis-11957	13	23	and	and	CCONJ
fcis-11957	13	24	algorithms	algorithm	NOUN
fcis-11957	13	25	to	to	PART
fcis-11957	13	26	assist	assist	VERB
fcis-11957	13	27	in	in	ADP
fcis-11957	13	28	solving	solve	VERB
fcis-11957	13	29	the	the	DET
fcis-11957	13	30	problem	problem	NOUN
fcis-11957	13	31	of	of	ADP
fcis-11957	13	32	identifying	identify	VERB
fcis-11957	13	33	glass	glass	NOUN
fcis-11957	13	34	artifacts	artifact	NOUN
fcis-11957	13	35	,	,	PUNCT
fcis-11957	13	36	so	so	SCONJ
fcis-11957	13	37	that	that	SCONJ
fcis-11957	13	38	the	the	DET
fcis-11957	13	39	difficulty	difficulty	NOUN
fcis-11957	13	40	of	of	ADP
fcis-11957	13	41	their	their	PRON
fcis-11957	13	42	identification	identification	NOUN
fcis-11957	13	43	can	can	AUX
fcis-11957	13	44	be	be	AUX
fcis-11957	13	45	further	far	ADV
fcis-11957	13	46	alleviated	alleviate	VERB
fcis-11957	13	47	and	and	CCONJ
fcis-11957	13	48	helped	help	VERB
fcis-11957	13	49	.	.	PUNCT
fcis-11957	14	1	2	2	X
fcis-11957	14	2	.	.	X
fcis-11957	14	3	problem	problem	NOUN
fcis-11957	14	4	description	description	NOUN
fcis-11957	14	5	the	the	DET
fcis-11957	14	6	main	main	ADJ
fcis-11957	14	7	raw	raw	ADJ
fcis-11957	14	8	material	material	NOUN
fcis-11957	14	9	of	of	ADP
fcis-11957	14	10	glass	glass	NOUN
fcis-11957	14	11	is	be	AUX
fcis-11957	14	12	quartz	quartz	NOUN
fcis-11957	14	13	sand	sand	NOUN
fcis-11957	14	14	,	,	PUNCT
fcis-11957	14	15	the	the	DET
fcis-11957	14	16	main	main	ADJ
fcis-11957	14	17	chemical	chemical	NOUN
fcis-11957	14	18	composition	composition	NOUN
fcis-11957	14	19	of	of	ADP
fcis-11957	14	20	which	which	PRON
fcis-11957	14	21	is	be	AUX
fcis-11957	14	22	sio2	sio2	PROPN
fcis-11957	14	23	,	,	PUNCT
fcis-11957	14	24	and	and	CCONJ
fcis-11957	14	25	due	due	ADP
fcis-11957	14	26	to	to	ADP
fcis-11957	14	27	the	the	DET
fcis-11957	14	28	high	high	ADJ
fcis-11957	14	29	melting	melting	NOUN
fcis-11957	14	30	point	point	NOUN
fcis-11957	14	31	of	of	ADP
fcis-11957	14	32	pure	pure	ADJ
fcis-11957	14	33	quartz	quartz	NOUN
fcis-11957	14	34	sand	sand	NOUN
fcis-11957	14	35	,	,	PUNCT
fcis-11957	14	36	fluxes	flux	NOUN
fcis-11957	14	37	are	be	AUX
fcis-11957	14	38	added	add	VERB
fcis-11957	14	39	during	during	ADP
fcis-11957	14	40	refining	refining	NOUN
fcis-11957	14	41	to	to	PART
fcis-11957	14	42	lower	lower	VERB
fcis-11957	14	43	the	the	DET
fcis-11957	14	44	melting	melting	NOUN
fcis-11957	14	45	temperature	temperature	NOUN
fcis-11957	14	46	.	.	PUNCT
fcis-11957	15	1	the	the	DET
fcis-11957	15	2	fluxes	flux	NOUN
fcis-11957	15	3	commonly	commonly	ADV
fcis-11957	15	4	used	use	VERB
fcis-11957	15	5	in	in	ADP
fcis-11957	15	6	ancient	ancient	ADJ
fcis-11957	15	7	times	time	NOUN
fcis-11957	15	8	were	be	AUX
fcis-11957	15	9	grass	grass	NOUN
fcis-11957	15	10	ash	ash	NOUN
fcis-11957	15	11	,	,	PUNCT
fcis-11957	15	12	natural	natural	ADJ
fcis-11957	15	13	alkali	alkali	ADJ
fcis-11957	15	14	,	,	PUNCT
fcis-11957	15	15	saltpeter	saltpeter	NOUN
fcis-11957	15	16	and	and	CCONJ
fcis-11957	15	17	lead	lead	VERB
fcis-11957	15	18	ore	ore	NOUN
fcis-11957	15	19	,	,	PUNCT
fcis-11957	15	20	etc	etc	X
fcis-11957	15	21	.	.	X
fcis-11957	15	22	limestone	limestone	NOUN
fcis-11957	15	23	was	be	AUX
fcis-11957	15	24	added	add	VERB
fcis-11957	15	25	as	as	ADP
fcis-11957	15	26	a	a	DET
fcis-11957	15	27	stabilizer	stabilizer	NOUN
fcis-11957	15	28	,	,	PUNCT
fcis-11957	15	29	which	which	PRON
fcis-11957	15	30	was	be	AUX
fcis-11957	15	31	converted	convert	VERB
fcis-11957	15	32	to	to	ADP
fcis-11957	15	33	cao	cao	PROPN
fcis-11957	15	34	after	after	ADP
fcis-11957	15	35	calcination	calcination	NOUN
fcis-11957	15	36	.	.	PUNCT
fcis-11957	16	1	the	the	DET
fcis-11957	16	2	main	main	ADJ
fcis-11957	16	3	chemical	chemical	NOUN
fcis-11957	16	4	composition	composition	NOUN
fcis-11957	16	5	of	of	ADP
fcis-11957	16	6	the	the	DET
fcis-11957	16	7	fluxes	flux	NOUN
fcis-11957	16	8	added	add	VERB
fcis-11957	16	9	differed	differ	VERB
fcis-11957	16	10	.	.	PUNCT
fcis-11957	17	1	for	for	ADP
fcis-11957	17	2	example	example	NOUN
fcis-11957	17	3	,	,	PUNCT
fcis-11957	17	4	lead	lead	ADJ
fcis-11957	17	5	barium	barium	NOUN
fcis-11957	17	6	glass	glass	NOUN
fcis-11957	17	7	adds	add	VERB
fcis-11957	17	8	lead	lead	VERB
fcis-11957	17	9	ore	ore	NOUN
fcis-11957	17	10	as	as	ADP
fcis-11957	17	11	a	a	DET
fcis-11957	17	12	flux	flux	NOUN
fcis-11957	17	13	in	in	ADP
fcis-11957	17	14	the	the	DET
fcis-11957	17	15	firing	firing	NOUN
fcis-11957	17	16	process	process	NOUN
fcis-11957	17	17	,	,	PUNCT
fcis-11957	17	18	and	and	CCONJ
fcis-11957	17	19	its	its	PRON
fcis-11957	17	20	content	content	NOUN
fcis-11957	17	21	of	of	ADP
fcis-11957	17	22	pbo	pbo	NOUN
fcis-11957	17	23	and	and	CCONJ
fcis-11957	17	24	bao	bao	PROPN
fcis-11957	17	25	is	be	AUX
fcis-11957	17	26	high	high	ADJ
fcis-11957	17	27	,	,	PUNCT
fcis-11957	17	28	which	which	PRON
fcis-11957	17	29	is	be	AUX
fcis-11957	17	30	usually	usually	ADV
fcis-11957	17	31	considered	consider	VERB
fcis-11957	17	32	as	as	ADP
fcis-11957	17	33	our	our	PRON
fcis-11957	17	34	own	own	ADJ
fcis-11957	17	35	invented	invent	VERB
fcis-11957	17	36	glass	glass	NOUN
fcis-11957	17	37	species	specie	NOUN
fcis-11957	17	38	,	,	PUNCT
fcis-11957	17	39	and	and	CCONJ
fcis-11957	17	40	the	the	DET
fcis-11957	17	41	glass	glass	NOUN
fcis-11957	17	42	of	of	ADP
fcis-11957	17	43	chu	chu	PROPN
fcis-11957	17	44	culture	culture	NOUN
fcis-11957	17	45	is	be	AUX
fcis-11957	17	46	mainly	mainly	ADV
fcis-11957	17	47	lead	lead	ADJ
fcis-11957	17	48	barium	barium	NOUN
fcis-11957	17	49	glass	glass	NOUN
fcis-11957	17	50	.	.	PUNCT
fcis-11957	18	1	potassium	potassium	NOUN
fcis-11957	18	2	glass	glass	NOUN
fcis-11957	18	3	is	be	AUX
fcis-11957	18	4	made	make	VERB
fcis-11957	18	5	by	by	ADP
fcis-11957	18	6	firing	fire	VERB
fcis-11957	18	7	substances	substance	NOUN
fcis-11957	18	8	with	with	ADP
fcis-11957	18	9	high	high	ADJ
fcis-11957	18	10	potassium	potassium	NOUN
fcis-11957	18	11	content	content	NOUN
fcis-11957	18	12	,	,	PUNCT
fcis-11957	18	13	such	such	ADJ
fcis-11957	18	14	as	as	ADP
fcis-11957	18	15	grass	grass	NOUN
fcis-11957	18	16	wood	wood	NOUN
fcis-11957	18	17	ash	ash	NOUN
fcis-11957	18	18	,	,	PUNCT
fcis-11957	18	19	as	as	ADP
fcis-11957	18	20	fluxes	flux	NOUN
fcis-11957	18	21	,	,	PUNCT
fcis-11957	18	22	and	and	CCONJ
fcis-11957	18	23	is	be	AUX
fcis-11957	18	24	mainly	mainly	ADV
fcis-11957	18	25	popular	popular	ADJ
fcis-11957	18	26	in	in	ADP
fcis-11957	18	27	lingnan	lingnan	ADJ
fcis-11957	18	28	,	,	PUNCT
fcis-11957	18	29	china	china	PROPN
fcis-11957	18	30	,	,	PUNCT
fcis-11957	18	31	and	and	CCONJ
fcis-11957	18	32	other	other	ADJ
fcis-11957	18	33	regions	region	NOUN
fcis-11957	18	34	in	in	ADP
fcis-11957	18	35	southeast	southeast	PROPN
fcis-11957	18	36	asia	asia	PROPN
fcis-11957	18	37	and	and	CCONJ
fcis-11957	18	38	india	india	PROPN
fcis-11957	18	39	.	.	PUNCT
fcis-11957	19	1	in	in	ADP
fcis-11957	19	2	this	this	DET
fcis-11957	19	3	context	context	NOUN
fcis-11957	19	4	,	,	PUNCT
fcis-11957	19	5	we	we	PRON
fcis-11957	19	6	intend	intend	VERB
fcis-11957	19	7	to	to	PART
fcis-11957	19	8	analyze	analyze	VERB
fcis-11957	19	9	the	the	DET
fcis-11957	19	10	chemical	chemical	NOUN
fcis-11957	19	11	composition	composition	NOUN
fcis-11957	19	12	of	of	ADP
fcis-11957	19	13	an	an	DET
fcis-11957	19	14	existing	exist	VERB
fcis-11957	19	15	group	group	NOUN
fcis-11957	19	16	of	of	ADP
fcis-11957	19	17	glass	glass	NOUN
fcis-11957	19	18	artifacts	artifact	NOUN
fcis-11957	19	19	of	of	ADP
fcis-11957	19	20	unknown	unknown	ADJ
fcis-11957	19	21	category	category	NOUN
fcis-11957	19	22	,	,	PUNCT
fcis-11957	19	23	identify	identify	VERB
fcis-11957	19	24	the	the	DET
fcis-11957	19	25	type	type	NOUN
fcis-11957	19	26	to	to	PART
fcis-11957	19	27	which	which	PRON
fcis-11957	19	28	they	they	PRON
fcis-11957	19	29	belong	belong	VERB
fcis-11957	19	30	,	,	PUNCT
fcis-11957	19	31	and	and	CCONJ
fcis-11957	19	32	analyze	analyze	VERB
fcis-11957	19	33	the	the	DET
fcis-11957	19	34	sensitivity	sensitivity	NOUN
fcis-11957	19	35	of	of	ADP
fcis-11957	19	36	the	the	DET
fcis-11957	19	37	classification	classification	NOUN
fcis-11957	19	38	results	result	NOUN
fcis-11957	19	39	.	.	PUNCT
fcis-11957	20	1	3	3	X
fcis-11957	20	2	.	.	X
fcis-11957	20	3	modeling	modeling	NOUN
fcis-11957	20	4	and	and	CCONJ
fcis-11957	20	5	solving	solve	VERB
fcis-11957	20	6	problem	problem	NOUN
fcis-11957	20	7	2	2	NUM
fcis-11957	20	8	3.1	3.1	NUM
fcis-11957	20	9	.	.	PUNCT
fcis-11957	21	1	screening	screen	VERB
fcis-11957	21	2	data	datum	NOUN
fcis-11957	21	3	by	by	ADP
fcis-11957	21	4	anova	anova	PROPN
fcis-11957	21	5	step1.anova	step1.anova	X
fcis-11957	22	1	[	[	X
fcis-11957	22	2	1	1	NUM
fcis-11957	22	3	]	]	PUNCT
fcis-11957	22	4	is	be	AUX
fcis-11957	22	5	generally	generally	ADV
fcis-11957	22	6	used	use	VERB
fcis-11957	22	7	for	for	ADP
fcis-11957	22	8	significant	significant	ADJ
fcis-11957	22	9	tests	test	NOUN
fcis-11957	22	10	of	of	ADP
fcis-11957	22	11	differences	difference	NOUN
fcis-11957	22	12	in	in	ADP
fcis-11957	22	13	means	mean	NOUN
fcis-11957	22	14	of	of	ADP
fcis-11957	22	15	two	two	NUM
fcis-11957	22	16	and	and	CCONJ
fcis-11957	22	17	more	more	ADJ
fcis-11957	22	18	samples	sample	NOUN
fcis-11957	22	19	(	(	PUNCT
fcis-11957	22	20	i.e.	i.e.	X
fcis-11957	22	21	,	,	PUNCT
fcis-11957	22	22	factors	factor	NOUN
fcis-11957	22	23	)	)	PUNCT
fcis-11957	22	24	.	.	PUNCT
fcis-11957	23	1	among	among	ADP
fcis-11957	23	2	them	they	PRON
fcis-11957	23	3	,	,	PUNCT
fcis-11957	23	4	we	we	PRON
fcis-11957	23	5	choose	choose	VERB
fcis-11957	23	6	one	one	NUM
fcis-11957	23	7	-	-	PUNCT
fcis-11957	23	8	way	way	NOUN
fcis-11957	23	9	anova	anova	X
fcis-11957	23	10	in	in	ADP
fcis-11957	23	11	whether	whether	SCONJ
fcis-11957	23	12	there	there	PRON
fcis-11957	23	13	is	be	VERB
fcis-11957	23	14	a	a	DET
fcis-11957	23	15	significant	significant	ADJ
fcis-11957	23	16	difference	difference	NOUN
fcis-11957	23	17	between	between	ADP
fcis-11957	23	18	different	different	ADJ
fcis-11957	23	19	types	type	NOUN
fcis-11957	23	20	of	of	ADP
fcis-11957	23	21	glass	glass	NOUN
fcis-11957	23	22	for	for	ADP
fcis-11957	23	23	each	each	PRON
fcis-11957	23	24	of	of	ADP
fcis-11957	23	25	its	its	PRON
fcis-11957	23	26	chemical	chemical	ADJ
fcis-11957	23	27	components	component	NOUN
fcis-11957	23	28	.	.	PUNCT
fcis-11957	24	1	step	step	NOUN
fcis-11957	24	2	2	2	NUM
fcis-11957	24	3	.	.	PUNCT
fcis-11957	24	4	mathematical	mathematical	ADJ
fcis-11957	24	5	model	model	NOUN
fcis-11957	24	6	in	in	ADP
fcis-11957	24	7	equation	equation	NOUN
fcis-11957	24	8	(	(	PUNCT
fcis-11957	24	9	6	6	NUM
fcis-11957	24	10	)	)	PUNCT
fcis-11957	24	11	,	,	PUNCT
fcis-11957	24	12	is	be	AUX
fcis-11957	24	13	the	the	DET
fcis-11957	24	14	matrix	matrix	NOUN
fcis-11957	24	15	of	of	ADP
fcis-11957	24	16	the	the	DET
fcis-11957	24	17	corresponding	corresponding	ADJ
fcis-11957	24	18	chemical	chemical	NOUN
fcis-11957	24	19	components	component	NOUN
fcis-11957	24	20	,	,	PUNCT
fcis-11957	24	21	is	be	AUX
fcis-11957	24	22	the	the	DET
fcis-11957	24	23	overall	overall	ADJ
fcis-11957	24	24	mean	mean	NOUN
fcis-11957	24	25	,	,	PUNCT
fcis-11957	24	26	and	and	CCONJ
fcis-11957	24	27	is	be	AUX
fcis-11957	24	28	the	the	DET
fcis-11957	24	29	effect	effect	NOUN
fcis-11957	24	30	of	of	ADP
fcis-11957	24	31	the	the	DET
fcis-11957	24	32	level	level	NOUN
fcis-11957	24	33	on	on	ADP
fcis-11957	24	34	the	the	DET
fcis-11957	24	35	test	test	NOUN
fcis-11957	24	36	index	index	NOUN
fcis-11957	24	37	.	.	PUNCT
fcis-11957	25	1	(	(	PUNCT
fcis-11957	25	2	1	1	X
fcis-11957	25	3	)	)	PUNCT
fcis-11957	25	4	this	this	PRON
fcis-11957	25	5	leads	lead	VERB
fcis-11957	25	6	to	to	ADP
fcis-11957	25	7	the	the	DET
fcis-11957	25	8	results	result	NOUN
fcis-11957	25	9	of	of	ADP
fcis-11957	25	10	the	the	DET
fcis-11957	25	11	analysis	analysis	NOUN
fcis-11957	25	12	of	of	ADP
fcis-11957	25	13	the	the	DET
fcis-11957	25	14	normality	normality	NOUN
fcis-11957	25	15	test	test	NOUN
fcis-11957	25	16	of	of	ADP
fcis-11957	25	17	the	the	DET
fcis-11957	25	18	quantitative	quantitative	ADJ
fcis-11957	25	19	variables	variable	NOUN
fcis-11957	25	20	for	for	ADP
fcis-11957	25	21	each	each	DET
fcis-11957	25	22	chemical	chemical	NOUN
fcis-11957	25	23	component	component	NOUN
fcis-11957	25	24	(	(	PUNCT
fcis-11957	25	25	see	see	VERB
fcis-11957	25	26	appendix	appendix	ADJ
fcis-11957	25	27	9	9	NUM
fcis-11957	25	28	)	)	PUNCT
fcis-11957	25	29	step3.f	step3.f	VERB
fcis-11957	25	30	test	test	NOUN
fcis-11957	25	31	method	method	NOUN
fcis-11957	25	32	101	101	NUM
fcis-11957	25	33	for	for	ADP
fcis-11957	25	34	this	this	PRON
fcis-11957	25	35	,	,	PUNCT
fcis-11957	25	36	we	we	PRON
fcis-11957	25	37	also	also	ADV
fcis-11957	25	38	need	need	VERB
fcis-11957	25	39	to	to	PART
fcis-11957	25	40	analyze	analyze	VERB
fcis-11957	25	41	by	by	ADP
fcis-11957	25	42	the	the	DET
fcis-11957	25	43	f	f	NOUN
fcis-11957	25	44	-	-	PUNCT
fcis-11957	25	45	test	test	NOUN
fcis-11957	25	46	method	method	NOUN
fcis-11957	25	47	,	,	PUNCT
fcis-11957	25	48	as	as	SCONJ
fcis-11957	25	49	,	,	PUNCT
fcis-11957	25	50	,	,	PUNCT
fcis-11957	25	51	(	(	PUNCT
fcis-11957	25	52	2	2	X
fcis-11957	25	53	)	)	PUNCT
fcis-11957	25	54	we	we	PRON
fcis-11957	25	55	then	then	ADV
fcis-11957	25	56	analyzed	analyze	VERB
fcis-11957	25	57	the	the	DET
fcis-11957	25	58	results	result	NOUN
fcis-11957	25	59	of	of	ADP
fcis-11957	25	60	the	the	DET
fcis-11957	25	61	chi	chi	NOUN
fcis-11957	25	62	-	-	PUNCT
fcis-11957	25	63	squared	square	VERB
fcis-11957	25	64	test	test	NOUN
fcis-11957	25	65	by	by	ADP
fcis-11957	25	66	spss	spss	PROPN
fcis-11957	25	67	as	as	SCONJ
fcis-11957	25	68	shown	show	VERB
fcis-11957	25	69	in	in	ADP
fcis-11957	25	70	fig	fig	NOUN
fcis-11957	25	71	:	:	PUNCT
fcis-11957	25	72	table	table	NOUN
fcis-11957	25	73	1	1	NUM
fcis-11957	25	74	.	.	PUNCT
fcis-11957	25	75	results	result	NOUN
fcis-11957	25	76	of	of	ADP
fcis-11957	25	77	chi	chi	ADJ
fcis-11957	25	78	-	-	PUNCT
fcis-11957	25	79	square	square	ADJ
fcis-11957	25	80	test	test	NOUN
fcis-11957	25	81	type	type	NOUN
fcis-11957	25	82	(	(	PUNCT
fcis-11957	25	83	standard	standard	ADJ
fcis-11957	25	84	deviation	deviation	NOUN
fcis-11957	25	85	)	)	PUNCT
fcis-11957	26	1	f	f	PROPN
fcis-11957	26	2	p	p	X
fcis-11957	26	3	high	high	ADJ
fcis-11957	26	4	potassium	potassium	NOUN
fcis-11957	26	5	(	(	PUNCT
fcis-11957	26	6	n=18	n=18	NOUN
fcis-11957	26	7	)	)	PUNCT
fcis-11957	26	8	lead	lead	NOUN
fcis-11957	26	9	barium(n=49	barium(n=49	PROPN
fcis-11957	26	10	)	)	PUNCT
fcis-11957	26	11	bao	bao	VERB
fcis-11957	26	12	0.842	0.842	NUM
fcis-11957	26	13	8.331	8.331	NUM
fcis-11957	26	14	12.256	12.256	NUM
fcis-11957	26	15	0.001	0.001	NUM
fcis-11957	26	16	*	*	PUNCT
fcis-11957	26	17	*	*	PUNCT
fcis-11957	26	18	*	*	PUNCT
fcis-11957	26	19	pbo	pbo	VERB
fcis-11957	26	20	0.514	0.514	NUM
fcis-11957	26	21	14.947	14.947	NUM
fcis-11957	26	22	42.508	42.508	NUM
fcis-11957	26	23	0.000	0.000	NUM
fcis-11957	26	24	*	*	PUNCT
fcis-11957	26	25	*	*	PUNCT
fcis-11957	26	26	*	*	PUNCT
fcis-11957	26	27	k2o	k2o	NOUN
fcis-11957	26	28	5.308	5.308	NUM
fcis-11957	26	29	0.276	0.276	NUM
fcis-11957	26	30	239.432	239.432	NUM
fcis-11957	26	31	0.000	0.000	NUM
fcis-11957	26	32	*	*	PUNCT
fcis-11957	26	33	*	*	PUNCT
fcis-11957	26	34	*	*	PUNCT
fcis-11957	26	35	so2	so2	PROPN
fcis-11957	26	36	0.157	0.157	NUM
fcis-11957	26	37	3.139	3.139	NUM
fcis-11957	26	38	4.026	4.026	NUM
fcis-11957	26	39	0.049	0.049	NUM
fcis-11957	26	40	*	*	PUNCT
fcis-11957	26	41	*	*	PUNCT
fcis-11957	26	42	cao	cao	PROPN
fcis-11957	27	1	3.308	3.308	NUM
fcis-11957	27	2	1.635	1.635	NUM
fcis-11957	27	3	43.324	43.324	NUM
fcis-11957	27	4	0.000	0.000	NUM
fcis-11957	27	5	*	*	PUNCT
fcis-11957	27	6	*	*	PUNCT
fcis-11957	27	7	*	*	PUNCT
fcis-11957	27	8	cuo	cuo	PROPN
fcis-11957	27	9	1.492	1.492	NUM
fcis-11957	27	10	2.47	2.47	NUM
fcis-11957	27	11	1.605	1.605	NUM
fcis-11957	27	12	0.21	0.21	NUM
fcis-11957	27	13	mgo	mgo	NOUN
fcis-11957	27	14	0.712	0.712	NUM
fcis-11957	27	15	0.63	0.63	NUM
fcis-11957	27	16	0.825	0.825	NUM
fcis-11957	27	17	0.367	0.367	NUM
fcis-11957	27	18	sro	sro	NOUN
fcis-11957	27	19	0.044	0.044	NUM
fcis-11957	27	20	0.264	0.264	NUM
fcis-11957	27	21	17.131	17.131	NUM
fcis-11957	27	22	0.000	0.000	NUM
fcis-11957	27	23	*	*	PUNCT
fcis-11957	27	24	*	*	PUNCT
fcis-11957	27	25	*	*	PUNCT
fcis-11957	27	26	sio2	sio2	PROPN
fcis-11957	27	27	14.467	14.467	NUM
fcis-11957	27	28	18.646	18.646	NUM
fcis-11957	27	29	1.711	1.711	NUM
fcis-11957	27	30	0.196	0.196	NUM
fcis-11957	27	31	sno2	sno2	PROPN
fcis-11957	27	32	0.556	0.556	NUM
fcis-11957	27	33	0.213	0.213	NUM
fcis-11957	27	34	3.026	3.026	NUM
fcis-11957	27	35	0.087	0.087	NUM
fcis-11957	27	36	*	*	PUNCT
fcis-11957	27	37	p2o5	p2o5	ADP
fcis-11957	27	38	1.281	1.281	NUM
fcis-11957	27	39	3.909	3.909	NUM
fcis-11957	27	40	23.493	23.493	NUM
fcis-11957	27	41	0.000	0.000	NUM
fcis-11957	27	42	*	*	PUNCT
fcis-11957	28	1	*	*	PUNCT
fcis-11957	28	2	*	*	PUNCT
fcis-11957	28	3	na2o	na2o	ADP
fcis-11957	28	4	1.089	1.089	NUM
fcis-11957	28	5	1.813	1.813	NUM
fcis-11957	28	6	2.772	2.772	NUM
fcis-11957	28	7	0.101	0.101	NUM
fcis-11957	28	8	fe2o3	fe2o3	PROPN
fcis-11957	28	9	1.566	1.566	NUM
fcis-11957	28	10	0.948	0.948	NUM
fcis-11957	28	11	7.739	7.739	NUM
fcis-11957	28	12	0.007	0.007	NUM
fcis-11957	28	13	*	*	PUNCT
fcis-11957	28	14	*	*	PUNCT
fcis-11957	28	15	*	*	PUNCT
fcis-11957	28	16	al2o3	al2o3	PROPN
fcis-11957	28	17	3.077	3.077	NUM
fcis-11957	28	18	3.009	3.009	NUM
fcis-11957	28	19	0.852	0.852	NUM
fcis-11957	28	20	0.359	0.359	NUM
fcis-11957	28	21	*	*	PUNCT
fcis-11957	29	1	*	*	PUNCT
fcis-11957	29	2	at	at	ADP
fcis-11957	29	3	the	the	DET
fcis-11957	29	4	0.01	0.01	NUM
fcis-11957	29	5	level	level	NOUN
fcis-11957	29	6	(	(	PUNCT
fcis-11957	29	7	two	two	NUM
fcis-11957	29	8	-	-	PUNCT
fcis-11957	29	9	tailed	tail	VERB
fcis-11957	29	10	)	)	PUNCT
fcis-11957	29	11	,	,	PUNCT
fcis-11957	29	12	the	the	DET
fcis-11957	29	13	correlation	correlation	NOUN
fcis-11957	29	14	is	be	AUX
fcis-11957	29	15	significant	significant	ADJ
fcis-11957	29	16	.	.	PUNCT
fcis-11957	30	1	*	*	PUNCT
fcis-11957	30	2	at	at	ADP
fcis-11957	30	3	the	the	DET
fcis-11957	30	4	0.05	0.05	NUM
fcis-11957	30	5	level	level	NOUN
fcis-11957	30	6	(	(	PUNCT
fcis-11957	30	7	two	two	NUM
fcis-11957	30	8	-	-	PUNCT
fcis-11957	30	9	tailed	tail	VERB
fcis-11957	30	10	)	)	PUNCT
fcis-11957	30	11	,	,	PUNCT
fcis-11957	30	12	the	the	DET
fcis-11957	30	13	correlation	correlation	NOUN
fcis-11957	30	14	is	be	AUX
fcis-11957	30	15	significant	significant	ADJ
fcis-11957	30	16	.	.	PUNCT
fcis-11957	31	1	it	it	PRON
fcis-11957	31	2	can	can	AUX
fcis-11957	31	3	be	be	AUX
fcis-11957	31	4	learned	learn	VERB
fcis-11957	31	5	that	that	SCONJ
fcis-11957	31	6	the	the	DET
fcis-11957	31	7	p	p	NOUN
fcis-11957	31	8	-	-	PUNCT
fcis-11957	31	9	values	value	NOUN
fcis-11957	31	10	of	of	ADP
fcis-11957	31	11	magnesium	magnesium	NOUN
fcis-11957	31	12	oxide	oxide	NOUN
fcis-11957	31	13	,	,	PUNCT
fcis-11957	31	14	sodium	sodium	NOUN
fcis-11957	31	15	oxide	oxide	NOUN
fcis-11957	31	16	,	,	PUNCT
fcis-11957	31	17	copper	copper	NOUN
fcis-11957	31	18	oxide	oxide	NOUN
fcis-11957	31	19	,	,	PUNCT
fcis-11957	31	20	tin	tin	NOUN
fcis-11957	31	21	dioxide	dioxide	NOUN
fcis-11957	31	22	,	,	PUNCT
fcis-11957	31	23	and	and	CCONJ
fcis-11957	31	24	aluminum	aluminum	NOUN
fcis-11957	31	25	oxide	oxide	NOUN
fcis-11957	31	26	among	among	ADP
fcis-11957	31	27	them	they	PRON
fcis-11957	31	28	are	be	AUX
fcis-11957	31	29	all	all	ADV
fcis-11957	31	30	greater	great	ADJ
fcis-11957	31	31	than	than	ADP
fcis-11957	31	32	0.05	0.05	NUM
fcis-11957	31	33	,	,	PUNCT
fcis-11957	31	34	so	so	SCONJ
fcis-11957	31	35	they	they	PRON
fcis-11957	31	36	are	be	AUX
fcis-11957	31	37	not	not	PART
fcis-11957	31	38	statistically	statistically	ADV
fcis-11957	31	39	significant	significant	ADJ
fcis-11957	31	40	,	,	PUNCT
fcis-11957	31	41	so	so	SCONJ
fcis-11957	31	42	it	it	PRON
fcis-11957	31	43	can	can	AUX
fcis-11957	31	44	be	be	AUX
fcis-11957	31	45	roughly	roughly	ADV
fcis-11957	31	46	stated	state	VERB
fcis-11957	31	47	that	that	SCONJ
fcis-11957	31	48	there	there	PRON
fcis-11957	31	49	are	be	VERB
fcis-11957	31	50	no	no	DET
fcis-11957	31	51	significant	significant	ADJ
fcis-11957	31	52	differences	difference	NOUN
fcis-11957	31	53	between	between	ADP
fcis-11957	31	54	different	different	ADJ
fcis-11957	31	55	types	type	NOUN
fcis-11957	31	56	of	of	ADP
fcis-11957	31	57	glasses	glass	NOUN
fcis-11957	31	58	in	in	ADP
fcis-11957	31	59	these	these	DET
fcis-11957	31	60	chemical	chemical	NOUN
fcis-11957	31	61	compositions	composition	NOUN
fcis-11957	31	62	.	.	PUNCT
fcis-11957	32	1	3.2	3.2	NUM
fcis-11957	32	2	.	.	PUNCT
fcis-11957	33	1	logistic	logistic	ADJ
fcis-11957	33	2	regression	regression	NOUN
fcis-11957	33	3	modeling	modeling	NOUN
fcis-11957	33	4	for	for	ADP
fcis-11957	33	5	dichotomous	dichotomous	ADJ
fcis-11957	33	6	classification	classification	NOUN
fcis-11957	33	7	(	(	PUNCT
fcis-11957	33	8	1	1	NUM
fcis-11957	33	9	)	)	PUNCT
fcis-11957	33	10	according	accord	VERB
fcis-11957	33	11	to	to	ADP
fcis-11957	33	12	the	the	DET
fcis-11957	33	13	requirements	requirement	NOUN
fcis-11957	33	14	of	of	ADP
fcis-11957	33	15	the	the	DET
fcis-11957	33	16	question	question	NOUN
fcis-11957	33	17	,	,	PUNCT
fcis-11957	33	18	we	we	PRON
fcis-11957	33	19	can	can	AUX
fcis-11957	33	20	establish	establish	VERB
fcis-11957	33	21	the	the	DET
fcis-11957	33	22	0	0	NUM
fcis-11957	33	23	-	-	SYM
fcis-11957	33	24	1	1	NUM
fcis-11957	33	25	variable	variable	NOUN
fcis-11957	33	26	to	to	PART
fcis-11957	33	27	complete	complete	VERB
fcis-11957	33	28	the	the	DET
fcis-11957	33	29	prediction	prediction	NOUN
fcis-11957	33	30	category	category	NOUN
fcis-11957	33	31	as	as	ADP
fcis-11957	33	32	the	the	DET
fcis-11957	33	33	dependent	dependent	ADJ
fcis-11957	33	34	variable	variable	NOUN
fcis-11957	33	35	,	,	PUNCT
fcis-11957	33	36	0	0	NUM
fcis-11957	33	37	indicates	indicate	VERB
fcis-11957	33	38	that	that	SCONJ
fcis-11957	33	39	the	the	DET
fcis-11957	33	40	unknown	unknown	ADJ
fcis-11957	33	41	type	type	NOUN
fcis-11957	33	42	of	of	ADP
fcis-11957	33	43	artifact	artifact	NOUN
fcis-11957	33	44	is	be	AUX
fcis-11957	33	45	high	high	ADJ
fcis-11957	33	46	potassium	potassium	NOUN
fcis-11957	33	47	glass	glass	NOUN
fcis-11957	33	48	,	,	PUNCT
fcis-11957	33	49	1	1	NUM
fcis-11957	33	50	indicates	indicate	VERB
fcis-11957	33	51	that	that	SCONJ
fcis-11957	33	52	the	the	DET
fcis-11957	33	53	unknown	unknown	ADJ
fcis-11957	33	54	type	type	NOUN
fcis-11957	33	55	of	of	ADP
fcis-11957	33	56	artifact	artifact	NOUN
fcis-11957	33	57	is	be	AUX
fcis-11957	33	58	lead	lead	ADJ
fcis-11957	33	59	barium	barium	NOUN
fcis-11957	33	60	glass	glass	NOUN
fcis-11957	33	61	,	,	PUNCT
fcis-11957	33	62	and	and	CCONJ
fcis-11957	33	63	the	the	DET
fcis-11957	33	64	chemical	chemical	NOUN
fcis-11957	33	65	composition	composition	NOUN
fcis-11957	33	66	that	that	PRON
fcis-11957	33	67	we	we	PRON
fcis-11957	33	68	previously	previously	ADV
fcis-11957	33	69	filtered	filter	VERB
fcis-11957	33	70	out	out	ADP
fcis-11957	33	71	through	through	ADP
fcis-11957	33	72	anova	anova	PROPN
fcis-11957	33	73	as	as	ADP
fcis-11957	33	74	the	the	DET
fcis-11957	33	75	independent	independent	ADJ
fcis-11957	33	76	variable	variable	NOUN
fcis-11957	33	77	,	,	PUNCT
fcis-11957	33	78	to	to	PART
fcis-11957	33	79	establish	establish	VERB
fcis-11957	33	80	a	a	DET
fcis-11957	33	81	silica	silica	NOUN
fcis-11957	33	82	,	,	PUNCT
fcis-11957	33	83	potassium	potassium	NOUN
fcis-11957	33	84	oxide	oxide	NOUN
fcis-11957	33	85	,	,	PUNCT
fcis-11957	33	86	calcium	calcium	NOUN
fcis-11957	33	87	oxide	oxide	NOUN
fcis-11957	33	88	,	,	PUNCT
fcis-11957	33	89	iron	iron	NOUN
fcis-11957	33	90	oxide	oxide	NOUN
fcis-11957	33	91	,	,	PUNCT
fcis-11957	33	92	lead	lead	VERB
fcis-11957	33	93	oxide	oxide	NOUN
fcis-11957	33	94	,	,	PUNCT
fcis-11957	33	95	barium	barium	NOUN
fcis-11957	33	96	oxide	oxide	NOUN
fcis-11957	33	97	,	,	PUNCT
fcis-11957	33	98	phosphorus	phosphorus	NOUN
fcis-11957	33	99	pentoxide	pentoxide	NOUN
fcis-11957	33	100	,	,	PUNCT
fcis-11957	33	101	and	and	CCONJ
fcis-11957	33	102	strontium	strontium	NOUN
fcis-11957	33	103	oxide	oxide	NOUN
fcis-11957	33	104	and	and	CCONJ
fcis-11957	33	105	sulfur	sulfur	NOUN
fcis-11957	33	106	dioxide	dioxide	NOUN
fcis-11957	33	107	in	in	ADP
fcis-11957	33	108	the	the	DET
fcis-11957	33	109	logistic	logistic	ADJ
fcis-11957	33	110	regression	regression	NOUN
fcis-11957	33	111	model	model	NOUN
fcis-11957	33	112	.	.	PUNCT
fcis-11957	34	1	therefore	therefore	ADV
fcis-11957	34	2	,	,	PUNCT
fcis-11957	34	3	when	when	SCONJ
fcis-11957	34	4	using	use	VERB
fcis-11957	34	5	the	the	DET
fcis-11957	34	6	logistic	logistic	ADJ
fcis-11957	34	7	regression	regression	NOUN
fcis-11957	34	8	model	model	NOUN
fcis-11957	34	9	[	[	X
fcis-11957	34	10	2	2	NUM
fcis-11957	34	11	-	-	SYM
fcis-11957	34	12	3	3	NUM
fcis-11957	34	13	]	]	PUNCT
fcis-11957	34	14	,	,	PUNCT
fcis-11957	34	15	the	the	DET
fcis-11957	34	16	dummy	dummy	ADJ
fcis-11957	34	17	variables	variable	NOUN
fcis-11957	34	18	were	be	AUX
fcis-11957	34	19	first	first	ADV
fcis-11957	34	20	processed	process	VERB
fcis-11957	34	21	by	by	ADP
fcis-11957	34	22	excel	excel	NOUN
fcis-11957	34	23	and	and	CCONJ
fcis-11957	34	24	then	then	ADV
fcis-11957	34	25	logistic	logistic	ADJ
fcis-11957	34	26	regression	regression	NOUN
fcis-11957	34	27	was	be	AUX
fcis-11957	34	28	performed	perform	VERB
fcis-11957	34	29	by	by	ADP
fcis-11957	34	30	spss	spss	PROPN
fcis-11957	34	31	to	to	PART
fcis-11957	34	32	predict	predict	VERB
fcis-11957	34	33	whether	whether	SCONJ
fcis-11957	34	34	the	the	DET
fcis-11957	34	35	unknown	unknown	ADJ
fcis-11957	34	36	artifacts	artifact	NOUN
fcis-11957	34	37	were	be	AUX
fcis-11957	34	38	of	of	ADP
fcis-11957	34	39	type	type	NOUN
fcis-11957	34	40	0	0	NUM
fcis-11957	34	41	or	or	CCONJ
fcis-11957	34	42	1	1	NUM
fcis-11957	34	43	.	.	PUNCT
fcis-11957	35	1	(	(	PUNCT
fcis-11957	35	2	2	2	X
fcis-11957	35	3	)	)	PUNCT
fcis-11957	35	4	step1	step1	PROPN
fcis-11957	35	5	.	.	PUNCT
fcis-11957	36	1	determine	determine	VERB
fcis-11957	36	2	the	the	DET
fcis-11957	36	3	probability	probability	NOUN
fcis-11957	36	4	of	of	ADP
fcis-11957	36	5	the	the	DET
fcis-11957	36	6	two	two	NUM
fcis-11957	36	7	-	-	PUNCT
fcis-11957	36	8	point	point	NOUN
fcis-11957	36	9	distribution	distribution	NOUN
fcis-11957	36	10	.	.	PUNCT
fcis-11957	37	1	(	(	PUNCT
fcis-11957	37	2	3	3	X
fcis-11957	37	3	)	)	PUNCT
fcis-11957	37	4	step2	step2	PROPN
fcis-11957	37	5	.	.	PUNCT
fcis-11957	38	1	take	take	VERB
fcis-11957	38	2	the	the	DET
fcis-11957	38	3	connection	connection	NOUN
fcis-11957	38	4	function	function	NOUN
fcis-11957	38	5	as	as	ADP
fcis-11957	38	6	function	function	NOUN
fcis-11957	38	7	.	.	PUNCT
fcis-11957	39	1	(	(	PUNCT
fcis-11957	39	2	4	4	X
fcis-11957	39	3	)	)	PUNCT
fcis-11957	39	4	step3	step3	PROPN
fcis-11957	39	5	.	.	PUNCT
fcis-11957	40	1	for	for	ADP
fcis-11957	40	2	the	the	DET
fcis-11957	40	3	nonlinear	nonlinear	ADJ
fcis-11957	40	4	model	model	NOUN
fcis-11957	40	5	,	,	PUNCT
fcis-11957	40	6	the	the	DET
fcis-11957	40	7	estimation	estimation	NOUN
fcis-11957	40	8	is	be	AUX
fcis-11957	40	9	performed	perform	VERB
fcis-11957	40	10	using	use	VERB
fcis-11957	40	11	the	the	DET
fcis-11957	40	12	maximum	maximum	ADJ
fcis-11957	40	13	likelihood	likelihood	NOUN
fcis-11957	40	14	estimation	estimation	NOUN
fcis-11957	40	15	method	method	NOUN
fcis-11957	40	16	.	.	PUNCT
fcis-11957	41	1	(	(	PUNCT
fcis-11957	41	2	5	5	X
fcis-11957	41	3	)	)	PUNCT
fcis-11957	41	4	step4	step4	PROPN
fcis-11957	41	5	.	.	PUNCT
fcis-11957	42	1	bring	bring	VERB
fcis-11957	42	2	the	the	DET
fcis-11957	42	3	regression	regression	NOUN
fcis-11957	42	4	coefficient	coefficient	NOUN
fcis-11957	42	5	to	to	ADP
fcis-11957	42	6	.	.	PUNCT
fcis-11957	43	1	(	(	PUNCT
fcis-11957	43	2	6	6	NUM
fcis-11957	43	3	)	)	PUNCT
fcis-11957	43	4	where	where	SCONJ
fcis-11957	43	5	is	be	AUX
fcis-11957	43	6	the	the	DET
fcis-11957	43	7	actual	actual	ADJ
fcis-11957	43	8	value	value	NOUN
fcis-11957	43	9	and	and	CCONJ
fcis-11957	43	10	is	be	AUX
fcis-11957	43	11	the	the	DET
fcis-11957	43	12	predicted	predict	VERB
fcis-11957	43	13	result	result	NOUN
fcis-11957	43	14	.	.	PUNCT
fcis-11957	44	1	where	where	SCONJ
fcis-11957	44	2	if	if	SCONJ
fcis-11957	44	3	the	the	DET
fcis-11957	44	4	predicted	predict	VERB
fcis-11957	44	5	value	value	NOUN
fcis-11957	44	6	is	be	AUX
fcis-11957	44	7	considered	consider	VERB
fcis-11957	44	8	its	its	PRON
fcis-11957	44	9	prediction	prediction	NOUN
fcis-11957	44	10	,	,	PUNCT
fcis-11957	44	11	otherwise	otherwise	ADV
fcis-11957	44	12	.	.	PUNCT
fcis-11957	45	1	after	after	ADP
fcis-11957	45	2	analyzing	analyze	VERB
fcis-11957	45	3	the	the	DET
fcis-11957	45	4	above	above	ADJ
fcis-11957	45	5	steps	step	NOUN
fcis-11957	45	6	,	,	PUNCT
fcis-11957	45	7	the	the	DET
fcis-11957	45	8	information	information	NOUN
fcis-11957	45	9	of	of	ADP
fcis-11957	45	10	the	the	DET
fcis-11957	45	11	components	component	NOUN
fcis-11957	45	12	filtered	filter	VERB
fcis-11957	45	13	by	by	ADP
fcis-11957	45	14	anova	anova	PROPN
fcis-11957	45	15	and	and	CCONJ
fcis-11957	45	16	the	the	DET
fcis-11957	45	17	corresponding	corresponding	ADJ
fcis-11957	45	18	information	information	NOUN
fcis-11957	45	19	of	of	ADP
fcis-11957	45	20	the	the	DET
fcis-11957	45	21	unknown	unknown	ADJ
fcis-11957	45	22	artifacts	artifact	NOUN
fcis-11957	45	23	are	be	AUX
fcis-11957	45	24	imported	import	VERB
fcis-11957	45	25	into	into	ADP
fcis-11957	45	26	spss	spss	PROPN
fcis-11957	45	27	for	for	ADP
fcis-11957	45	28	binary	binary	ADJ
fcis-11957	45	29	regression	regression	NOUN
fcis-11957	45	30	,	,	PUNCT
fcis-11957	45	31	and	and	CCONJ
fcis-11957	45	32	the	the	DET
fcis-11957	45	33	regression	regression	NOUN
fcis-11957	45	34	coefficients	coefficient	NOUN
fcis-11957	45	35	obtained	obtain	VERB
fcis-11957	45	36	are	be	AUX
fcis-11957	45	37	and	and	CCONJ
fcis-11957	45	38	the	the	DET
fcis-11957	45	39	constants	constant	NOUN
fcis-11957	45	40	are	be	AUX
fcis-11957	45	41	:	:	PUNCT
fcis-11957	45	42	table	table	NOUN
fcis-11957	45	43	2	2	NUM
fcis-11957	45	44	.	.	PUNCT
fcis-11957	46	1	regression	regression	NOUN
fcis-11957	46	2	coefficients	coefficient	NOUN
fcis-11957	46	3	corresponding	correspond	VERB
fcis-11957	46	4	to	to	ADP
fcis-11957	46	5	each	each	DET
fcis-11957	46	6	filtered	filter	VERB
fcis-11957	46	7	input	input	NOUN
fcis-11957	46	8	variable	variable	ADJ
fcis-11957	46	9	variables	variable	NOUN
fcis-11957	46	10	to	to	PART
fcis-11957	46	11	be	be	AUX
fcis-11957	46	12	entered	enter	VERB
fcis-11957	46	13	silicon	silicon	NOUN
fcis-11957	46	14	dioxide	dioxide	NOUN
fcis-11957	46	15	(	(	PUNCT
fcis-11957	46	16	sio2	sio2	PROPN
fcis-11957	46	17	)	)	PUNCT
fcis-11957	46	18	-0.198	-0.198	NOUN
fcis-11957	46	19	potassium	potassium	NOUN
fcis-11957	46	20	oxide	oxide	NOUN
fcis-11957	46	21	(	(	PUNCT
fcis-11957	46	22	k2o	k2o	NOUN
fcis-11957	46	23	)	)	PUNCT
fcis-11957	46	24	-1.131	-1.131	PUNCT
fcis-11957	46	25	calcium	calcium	NOUN
fcis-11957	46	26	oxide	oxide	NOUN
fcis-11957	46	27	(	(	PUNCT
fcis-11957	46	28	cao	cao	NOUN
fcis-11957	46	29	)	)	PUNCT
fcis-11957	46	30	-0.329	-0.329	PUNCT
fcis-11957	46	31	iron	iron	NOUN
fcis-11957	46	32	oxide	oxide	NOUN
fcis-11957	46	33	(	(	PUNCT
fcis-11957	46	34	fe2o3	fe2o3	PROPN
fcis-11957	46	35	)	)	PUNCT
fcis-11957	46	36	-0.87	-0.87	NUM
fcis-11957	46	37	lead	lead	NOUN
fcis-11957	46	38	oxide	oxide	NOUN
fcis-11957	46	39	(	(	PUNCT
fcis-11957	46	40	pbo	pbo	NOUN
fcis-11957	46	41	)	)	PUNCT
fcis-11957	46	42	1.545	1.545	NUM
fcis-11957	46	43	barium	barium	NOUN
fcis-11957	46	44	oxide	oxide	NOUN
fcis-11957	46	45	(	(	PUNCT
fcis-11957	46	46	bao	bao	PROPN
fcis-11957	46	47	)	)	PUNCT
fcis-11957	46	48	1.643	1.643	NUM
fcis-11957	46	49	phosphorus	phosphorus	NOUN
fcis-11957	46	50	pentoxide	pentoxide	NOUN
fcis-11957	46	51	(	(	PUNCT
fcis-11957	46	52	p2o5	p2o5	PROPN
fcis-11957	46	53	)	)	PUNCT
fcis-11957	46	54	-4.741	-4.741	PUNCT
fcis-11957	46	55	strontium	strontium	NOUN
fcis-11957	46	56	oxide	oxide	NOUN
fcis-11957	46	57	(	(	PUNCT
fcis-11957	46	58	sro	sro	NOUN
fcis-11957	46	59	)	)	PUNCT
fcis-11957	46	60	35.408	35.408	NUM
fcis-11957	46	61	sulfur	sulfur	NOUN
fcis-11957	46	62	dioxide	dioxide	NOUN
fcis-11957	46	63	(	(	PUNCT
fcis-11957	46	64	so2	so2	PROPN
fcis-11957	46	65	)	)	PUNCT
fcis-11957	46	66	-4.229	-4.229	PUNCT
fcis-11957	46	67	constants	constant	VERB
fcis-11957	46	68	2.005	2.005	NUM
fcis-11957	46	69	once	once	SCONJ
fcis-11957	46	70	the	the	DET
fcis-11957	46	71	regression	regression	NOUN
fcis-11957	46	72	coefficients	coefficient	NOUN
fcis-11957	46	73	are	be	AUX
fcis-11957	46	74	found	find	VERB
fcis-11957	46	75	,	,	PUNCT
fcis-11957	46	76	they	they	PRON
fcis-11957	46	77	are	be	AUX
fcis-11957	46	78	brought	bring	VERB
fcis-11957	46	79	into	into	ADP
fcis-11957	46	80	the	the	DET
fcis-11957	46	81	predicted	predict	VERB
fcis-11957	46	82	values	value	NOUN
fcis-11957	46	83	at	at	ADP
fcis-11957	46	84	to	to	PART
fcis-11957	46	85	obtain	obtain	VERB
fcis-11957	46	86	the	the	DET
fcis-11957	46	87	predicted	predict	VERB
fcis-11957	46	88	values	value	NOUN
fcis-11957	46	89	.	.	PUNCT
fcis-11957	47	1	then	then	ADV
fcis-11957	47	2	compare	compare	VERB
fcis-11957	47	3	with	with	ADP
fcis-11957	47	4	the	the	DET
fcis-11957	47	5	actual	actual	ADJ
fcis-11957	47	6	value	value	NOUN
fcis-11957	47	7	to	to	PART
fcis-11957	47	8	get	get	VERB
fcis-11957	47	9	the	the	DET
fcis-11957	47	10	following	follow	VERB
fcis-11957	47	11	table	table	NOUN
fcis-11957	47	12	:	:	PUNCT
fcis-11957	47	13	102	102	NUM
fcis-11957	47	14	table	table	NOUN
fcis-11957	47	15	3	3	NUM
fcis-11957	47	16	.	.	PUNCT
fcis-11957	47	17	results	result	NOUN
fcis-11957	47	18	of	of	ADP
fcis-11957	47	19	predicted	predict	VERB
fcis-11957	47	20	artifact	artifact	ADJ
fcis-11957	47	21	types	type	NOUN
fcis-11957	47	22	artifact	artifact	ADJ
fcis-11957	47	23	number	number	NOUN
fcis-11957	47	24	predicted	predict	VERB
fcis-11957	47	25	results	result	NOUN
fcis-11957	47	26	a1	a1	NOUN
fcis-11957	47	27	0	0	NUM
fcis-11957	47	28	high	high	ADJ
fcis-11957	47	29	potassium	potassium	NOUN
fcis-11957	47	30	a2	a2	NOUN
fcis-11957	47	31	0	0	NUM
fcis-11957	47	32	high	high	ADJ
fcis-11957	47	33	potassium	potassium	NOUN
fcis-11957	47	34	a3	a3	NOUN
fcis-11957	47	35	1	1	NUM
fcis-11957	47	36	lead	lead	NOUN
fcis-11957	47	37	barium	barium	NOUN
fcis-11957	47	38	a4	a4	NOUN
fcis-11957	47	39	0.99981	0.99981	NUM
fcis-11957	47	40	lead	lead	NOUN
fcis-11957	47	41	barium	barium	NOUN
fcis-11957	47	42	a5	a5	NOUN
fcis-11957	47	43	1	1	NUM
fcis-11957	47	44	lead	lead	NOUN
fcis-11957	47	45	barium	barium	NOUN
fcis-11957	47	46	a6	a6	NOUN
fcis-11957	47	47	0	0	NUM
fcis-11957	47	48	high	high	ADJ
fcis-11957	47	49	potassium	potassium	NOUN
fcis-11957	47	50	a7	a7	NOUN
fcis-11957	47	51	0	0	NUM
fcis-11957	47	52	high	high	ADJ
fcis-11957	47	53	potassium	potassium	NOUN
fcis-11957	47	54	a8	a8	NOUN
fcis-11957	47	55	1	1	NUM
fcis-11957	47	56	lead	lead	NOUN
fcis-11957	47	57	barium	barium	NOUN
fcis-11957	47	58	3.3	3.3	NUM
fcis-11957	47	59	.	.	PUNCT
fcis-11957	48	1	sensitivity	sensitivity	NOUN
fcis-11957	48	2	analysis	analysis	NOUN
fcis-11957	48	3	of	of	ADP
fcis-11957	48	4	the	the	DET
fcis-11957	48	5	model	model	NOUN
fcis-11957	48	6	the	the	DET
fcis-11957	48	7	above	above	ADV
fcis-11957	48	8	-	-	PUNCT
fcis-11957	48	9	mentioned	mention	VERB
fcis-11957	48	10	values	value	NOUN
fcis-11957	48	11	from	from	ADP
fcis-11957	48	12	the	the	DET
fcis-11957	48	13	anova	anova	PROPN
fcis-11957	48	14	screening	screening	NOUN
fcis-11957	48	15	showed	show	VERB
fcis-11957	48	16	that	that	SCONJ
fcis-11957	48	17	there	there	PRON
fcis-11957	48	18	were	be	VERB
fcis-11957	48	19	also	also	ADV
fcis-11957	48	20	some	some	DET
fcis-11957	48	21	values	value	NOUN
fcis-11957	48	22	with	with	ADP
fcis-11957	48	23	large	large	ADJ
fcis-11957	48	24	differences	difference	NOUN
fcis-11957	48	25	,	,	PUNCT
fcis-11957	48	26	and	and	CCONJ
fcis-11957	48	27	we	we	PRON
fcis-11957	48	28	extracted	extract	VERB
fcis-11957	48	29	the	the	DET
fcis-11957	48	30	difference	difference	NOUN
fcis-11957	48	31	data	datum	NOUN
fcis-11957	48	32	and	and	CCONJ
fcis-11957	48	33	then	then	ADV
fcis-11957	48	34	used	use	VERB
fcis-11957	48	35	spss	spss	PROPN
fcis-11957	48	36	to	to	PART
fcis-11957	48	37	get	get	VERB
fcis-11957	48	38	the	the	DET
fcis-11957	48	39	final	final	ADJ
fcis-11957	48	40	prediction	prediction	NOUN
fcis-11957	48	41	results	result	NOUN
fcis-11957	48	42	.	.	PUNCT
fcis-11957	49	1	i	i	PRON
fcis-11957	49	2	intend	intend	VERB
fcis-11957	49	3	to	to	PART
fcis-11957	49	4	extract	extract	VERB
fcis-11957	49	5	the	the	DET
fcis-11957	49	6	largest	large	ADJ
fcis-11957	49	7	and	and	CCONJ
fcis-11957	49	8	smallest	small	ADJ
fcis-11957	49	9	component	component	NOUN
fcis-11957	49	10	data	datum	NOUN
fcis-11957	49	11	to	to	PART
fcis-11957	49	12	see	see	VERB
fcis-11957	49	13	if	if	SCONJ
fcis-11957	49	14	it	it	PRON
fcis-11957	49	15	has	have	AUX
fcis-11957	49	16	changed	change	VERB
fcis-11957	49	17	(	(	PUNCT
fcis-11957	49	18	1	1	NUM
fcis-11957	49	19	for	for	ADP
fcis-11957	49	20	high	high	ADJ
fcis-11957	49	21	potassium	potassium	NOUN
fcis-11957	49	22	and	and	CCONJ
fcis-11957	49	23	0	0	NUM
fcis-11957	49	24	for	for	ADP
fcis-11957	49	25	lead	lead	NOUN
fcis-11957	49	26	and	and	CCONJ
fcis-11957	49	27	barium	barium	NOUN
fcis-11957	49	28	):	):	PUNCT
fcis-11957	49	29	table	table	NOUN
fcis-11957	49	30	4	4	NUM
fcis-11957	49	31	.	.	PUNCT
fcis-11957	49	32	results	result	NOUN
fcis-11957	49	33	after	after	ADP
fcis-11957	49	34	extraction	extraction	NOUN
fcis-11957	49	35	of	of	ADP
fcis-11957	49	36	sulfur	sulfur	NOUN
fcis-11957	49	37	dioxide	dioxide	NOUN
fcis-11957	49	38	artifact	artifact	NOUN
fcis-11957	49	39	number	number	NOUN
fcis-11957	49	40	y_hat	y_hat	PRON
fcis-11957	49	41	predicted	predict	VERB
fcis-11957	49	42	results	result	NOUN
fcis-11957	49	43	a1	a1	VERB
fcis-11957	49	44	0	0	NUM
fcis-11957	50	1	1	1	NUM
fcis-11957	50	2	a2	a2	PROPN
fcis-11957	50	3	0	0	NUM
fcis-11957	50	4	0	0	NUM
fcis-11957	50	5	a3	a3	NOUN
fcis-11957	50	6	1	1	NUM
fcis-11957	50	7	0	0	NUM
fcis-11957	50	8	a4	a4	NOUN
fcis-11957	50	9	0.99988	0.99988	NUM
fcis-11957	50	10	0	0	NUM
fcis-11957	50	11	a5	a5	X
fcis-11957	50	12	1	1	NUM
fcis-11957	50	13	0	0	NUM
fcis-11957	50	14	a6	a6	NOUN
fcis-11957	50	15	0	0	NUM
fcis-11957	50	16	1	1	NUM
fcis-11957	50	17	a7	a7	NOUN
fcis-11957	50	18	0	0	NUM
fcis-11957	50	19	1	1	NUM
fcis-11957	50	20	a8	a8	PROPN
fcis-11957	50	21	1	1	NUM
fcis-11957	50	22	0	0	NUM
fcis-11957	50	23	from	from	ADP
fcis-11957	50	24	the	the	DET
fcis-11957	50	25	above	above	ADJ
fcis-11957	50	26	two	two	NUM
fcis-11957	50	27	figures	figure	NOUN
fcis-11957	50	28	,	,	PUNCT
fcis-11957	50	29	it	it	PRON
fcis-11957	50	30	can	can	AUX
fcis-11957	50	31	be	be	AUX
fcis-11957	50	32	seen	see	VERB
fcis-11957	50	33	that	that	SCONJ
fcis-11957	50	34	the	the	DET
fcis-11957	50	35	extraction	extraction	NOUN
fcis-11957	50	36	of	of	ADP
fcis-11957	50	37	sulfur	sulfur	NOUN
fcis-11957	50	38	dioxide	dioxide	NOUN
fcis-11957	50	39	has	have	VERB
fcis-11957	50	40	no	no	DET
fcis-11957	50	41	effect	effect	NOUN
fcis-11957	50	42	on	on	ADP
fcis-11957	50	43	its	its	PRON
fcis-11957	50	44	results	result	NOUN
fcis-11957	50	45	,	,	PUNCT
fcis-11957	50	46	while	while	SCONJ
fcis-11957	50	47	the	the	DET
fcis-11957	50	48	extraction	extraction	NOUN
fcis-11957	50	49	of	of	ADP
fcis-11957	50	50	silica	silica	NOUN
fcis-11957	50	51	has	have	AUX
fcis-11957	50	52	produced	produce	VERB
fcis-11957	50	53	a	a	DET
fcis-11957	50	54	change	change	NOUN
fcis-11957	50	55	in	in	ADP
fcis-11957	50	56	its	its	PRON
fcis-11957	50	57	final	final	ADJ
fcis-11957	50	58	classification	classification	NOUN
fcis-11957	50	59	,	,	PUNCT
fcis-11957	50	60	with	with	ADP
fcis-11957	50	61	the	the	DET
fcis-11957	50	62	category	category	NOUN
fcis-11957	50	63	of	of	ADP
fcis-11957	50	64	a2	a2	PROPN
fcis-11957	50	65	changing	change	VERB
fcis-11957	50	66	from	from	ADP
fcis-11957	50	67	leadbarium	leadbarium	NOUN
fcis-11957	50	68	to	to	ADP
fcis-11957	50	69	high	high	ADJ
fcis-11957	50	70	potassium	potassium	NOUN
fcis-11957	50	71	,	,	PUNCT
fcis-11957	50	72	which	which	PRON
fcis-11957	50	73	leads	lead	VERB
fcis-11957	50	74	to	to	ADP
fcis-11957	50	75	the	the	DET
fcis-11957	50	76	assumption	assumption	NOUN
fcis-11957	50	77	that	that	SCONJ
fcis-11957	50	78	silica	silica	NOUN
fcis-11957	50	79	is	be	AUX
fcis-11957	50	80	a	a	DET
fcis-11957	50	81	subset	subset	NOUN
fcis-11957	50	82	of	of	ADP
fcis-11957	50	83	its	its	PRON
fcis-11957	50	84	sensitivity	sensitivity	NOUN
fcis-11957	50	85	factors	factor	NOUN
fcis-11957	50	86	.	.	PUNCT
fcis-11957	51	1	table	table	NOUN
fcis-11957	51	2	5	5	NUM
fcis-11957	51	3	.	.	PUNCT
fcis-11957	51	4	results	result	NOUN
fcis-11957	51	5	after	after	ADP
fcis-11957	51	6	extraction	extraction	NOUN
fcis-11957	51	7	of	of	ADP
fcis-11957	51	8	silica	silica	NOUN
fcis-11957	51	9	artifact	artifact	NOUN
fcis-11957	51	10	number	number	NOUN
fcis-11957	51	11	y_hat	y_hat	PRON
fcis-11957	51	12	predicted	predict	VERB
fcis-11957	51	13	results	result	NOUN
fcis-11957	51	14	a1	a1	VERB
fcis-11957	51	15	0	0	NUM
fcis-11957	51	16	1	1	NUM
fcis-11957	51	17	a2	a2	PROPN
fcis-11957	51	18	0	0	NUM
fcis-11957	51	19	1	1	NUM
fcis-11957	51	20	a3	a3	NOUN
fcis-11957	51	21	1	1	NUM
fcis-11957	51	22	0	0	NUM
fcis-11957	51	23	a4	a4	NOUN
fcis-11957	51	24	0.99997	0.99997	NUM
fcis-11957	51	25	0	0	NUM
fcis-11957	51	26	a5	a5	NOUN
fcis-11957	51	27	1	1	NUM
fcis-11957	51	28	0	0	NUM
fcis-11957	51	29	a6	a6	NOUN
fcis-11957	51	30	0	0	NUM
fcis-11957	51	31	0	0	NUM
fcis-11957	52	1	a7	a7	NOUN
fcis-11957	52	2	0	0	NUM
fcis-11957	52	3	1	1	NUM
fcis-11957	52	4	a8	a8	PROPN
fcis-11957	52	5	1	1	NUM
fcis-11957	52	6	0	0	NUM
fcis-11957	52	7	4	4	NUM
fcis-11957	52	8	.	.	PUNCT
fcis-11957	52	9	conclusion	conclusion	NOUN
fcis-11957	52	10	this	this	DET
fcis-11957	52	11	paper	paper	NOUN
fcis-11957	52	12	focuses	focus	VERB
fcis-11957	52	13	on	on	ADP
fcis-11957	52	14	the	the	DET
fcis-11957	52	15	application	application	NOUN
fcis-11957	52	16	of	of	ADP
fcis-11957	52	17	anova	anova	PROPN
fcis-11957	52	18	and	and	CCONJ
fcis-11957	52	19	dichotomous	dichotomous	ADJ
fcis-11957	52	20	logistic	logistic	ADJ
fcis-11957	52	21	regression	regression	NOUN
fcis-11957	52	22	model	model	NOUN
fcis-11957	52	23	algorithms	algorithm	NOUN
fcis-11957	52	24	.	.	PUNCT
fcis-11957	53	1	in	in	ADP
fcis-11957	53	2	the	the	DET
fcis-11957	53	3	study	study	NOUN
fcis-11957	53	4	,	,	PUNCT
fcis-11957	53	5	we	we	PRON
fcis-11957	53	6	positioned	position	VERB
fcis-11957	53	7	the	the	DET
fcis-11957	53	8	experimental	experimental	ADJ
fcis-11957	53	9	object	object	NOUN
fcis-11957	53	10	to	to	ADP
fcis-11957	53	11	the	the	DET
fcis-11957	53	12	identification	identification	NOUN
fcis-11957	53	13	of	of	ADP
fcis-11957	53	14	glass	glass	NOUN
fcis-11957	53	15	artifact	artifact	NOUN
fcis-11957	53	16	categories	category	NOUN
fcis-11957	53	17	,	,	PUNCT
fcis-11957	53	18	and	and	CCONJ
fcis-11957	53	19	in	in	ADP
fcis-11957	53	20	the	the	DET
fcis-11957	53	21	screening	screening	NOUN
fcis-11957	53	22	of	of	ADP
fcis-11957	53	23	its	its	PRON
fcis-11957	53	24	chemical	chemical	NOUN
fcis-11957	53	25	composition	composition	NOUN
fcis-11957	53	26	by	by	ADP
fcis-11957	53	27	one	one	NUM
fcis-11957	53	28	-	-	PUNCT
fcis-11957	53	29	way	way	NOUN
fcis-11957	53	30	anova	anova	X
fcis-11957	53	31	,	,	PUNCT
fcis-11957	53	32	it	it	PRON
fcis-11957	53	33	can	can	AUX
fcis-11957	53	34	be	be	AUX
fcis-11957	53	35	significantly	significantly	ADV
fcis-11957	53	36	found	find	VERB
fcis-11957	53	37	that	that	SCONJ
fcis-11957	53	38	some	some	PRON
fcis-11957	53	39	of	of	ADP
fcis-11957	53	40	the	the	DET
fcis-11957	53	41	chemical	chemical	ADJ
fcis-11957	53	42	components	component	NOUN
fcis-11957	53	43	do	do	AUX
fcis-11957	53	44	not	not	PART
fcis-11957	53	45	differ	differ	VERB
fcis-11957	53	46	significantly	significantly	ADV
fcis-11957	53	47	in	in	ADP
fcis-11957	53	48	different	different	ADJ
fcis-11957	53	49	glass	glass	NOUN
fcis-11957	53	50	artifact	artifact	NOUN
fcis-11957	53	51	categories	category	NOUN
fcis-11957	53	52	,	,	PUNCT
fcis-11957	53	53	and	and	CCONJ
fcis-11957	53	54	then	then	ADV
fcis-11957	53	55	the	the	DET
fcis-11957	53	56	former	former	ADJ
fcis-11957	53	57	screening	screening	NOUN
fcis-11957	53	58	results	result	NOUN
fcis-11957	53	59	of	of	ADP
fcis-11957	53	60	its	its	PRON
fcis-11957	53	61	classification	classification	NOUN
fcis-11957	53	62	identification	identification	NOUN
fcis-11957	53	63	by	by	ADP
fcis-11957	53	64	regression	regression	NOUN
fcis-11957	53	65	model	model	NOUN
fcis-11957	53	66	,	,	PUNCT
fcis-11957	53	67	and	and	CCONJ
fcis-11957	53	68	in	in	ADP
fcis-11957	53	69	order	order	NOUN
fcis-11957	53	70	to	to	PART
fcis-11957	53	71	make	make	VERB
fcis-11957	53	72	the	the	DET
fcis-11957	53	73	identification	identification	NOUN
fcis-11957	53	74	results	result	VERB
fcis-11957	53	75	less	less	ADJ
fcis-11957	53	76	error	error	NOUN
fcis-11957	53	77	,	,	PUNCT
fcis-11957	53	78	and	and	CCONJ
fcis-11957	53	79	after	after	ADP
fcis-11957	53	80	the	the	DET
fcis-11957	53	81	sensitivity	sensitivity	NOUN
fcis-11957	53	82	analysis	analysis	NOUN
fcis-11957	53	83	of	of	ADP
fcis-11957	53	84	its	its	PRON
fcis-11957	53	85	results	result	NOUN
fcis-11957	53	86	it	it	PRON
fcis-11957	53	87	is	be	AUX
fcis-11957	53	88	clear	clear	ADJ
fcis-11957	53	89	that	that	SCONJ
fcis-11957	53	90	sio2	sio2	PROPN
fcis-11957	53	91	is	be	AUX
fcis-11957	53	92	a	a	DET
fcis-11957	53	93	subset	subset	NOUN
fcis-11957	53	94	of	of	ADP
fcis-11957	53	95	the	the	DET
fcis-11957	53	96	sensitive	sensitive	ADJ
fcis-11957	53	97	factors	factor	NOUN
fcis-11957	53	98	in	in	ADP
fcis-11957	53	99	the	the	DET
fcis-11957	53	100	classification	classification	NOUN
fcis-11957	53	101	results	result	NOUN
fcis-11957	53	102	.	.	PUNCT
fcis-11957	54	1	in	in	ADP
fcis-11957	54	2	this	this	DET
fcis-11957	54	3	process	process	NOUN
fcis-11957	54	4	,	,	PUNCT
fcis-11957	54	5	the	the	DET
fcis-11957	54	6	feasibility	feasibility	NOUN
fcis-11957	54	7	and	and	CCONJ
fcis-11957	54	8	accuracy	accuracy	NOUN
fcis-11957	54	9	of	of	ADP
fcis-11957	54	10	these	these	DET
fcis-11957	54	11	modeling	modeling	NOUN
fcis-11957	54	12	algorithms	algorithm	NOUN
fcis-11957	54	13	for	for	ADP
fcis-11957	54	14	such	such	ADJ
fcis-11957	54	15	problems	problem	NOUN
fcis-11957	54	16	can	can	AUX
fcis-11957	54	17	be	be	AUX
fcis-11957	54	18	seen	see	VERB
fcis-11957	54	19	,	,	PUNCT
fcis-11957	54	20	and	and	CCONJ
fcis-11957	54	21	further	further	ADJ
fcis-11957	54	22	research	research	NOUN
fcis-11957	54	23	on	on	ADP
fcis-11957	54	24	such	such	ADJ
fcis-11957	54	25	modeling	modeling	NOUN
fcis-11957	54	26	algorithms	algorithm	NOUN
fcis-11957	54	27	can	can	AUX
fcis-11957	54	28	be	be	AUX
fcis-11957	54	29	developed	develop	VERB
fcis-11957	54	30	and	and	CCONJ
fcis-11957	54	31	explored	explore	VERB
fcis-11957	54	32	.	.	PUNCT
fcis-11957	55	1	acknowledgments	acknowledgment	NOUN
fcis-11957	55	2	the	the	DET
fcis-11957	55	3	authors	author	NOUN
fcis-11957	55	4	gratefully	gratefully	ADV
fcis-11957	55	5	acknowledge	acknowledge	VERB
fcis-11957	55	6	the	the	DET
fcis-11957	55	7	financial	financial	ADJ
fcis-11957	55	8	support	support	NOUN
fcis-11957	55	9	from	from	ADP
fcis-11957	55	10	innovation	innovation	NOUN
fcis-11957	55	11	and	and	CCONJ
fcis-11957	55	12	entrepreneurship	entrepreneurship	NOUN
fcis-11957	55	13	training	training	NOUN
fcis-11957	55	14	program	program	NOUN
fcis-11957	55	15	of	of	ADP
fcis-11957	55	16	wuhan	wuhan	PROPN
fcis-11957	55	17	business	business	PROPN
fcis-11957	55	18	university	university	PROPN
fcis-11957	55	19	(	(	PUNCT
fcis-11957	55	20	202211654165	202211654165	NUM
fcis-11957	55	21	)	)	PUNCT
fcis-11957	55	22	,	,	PUNCT
fcis-11957	55	23	ministry	ministry	PROPN
fcis-11957	55	24	of	of	ADP
fcis-11957	55	25	education	education	PROPN
fcis-11957	55	26	industry	industry	NOUN
fcis-11957	55	27	-	-	PUNCT
fcis-11957	55	28	university	university	NOUN
fcis-11957	55	29	cooperative	cooperative	ADJ
fcis-11957	55	30	education	education	NOUN
fcis-11957	55	31	project	project	NOUN
fcis-11957	55	32	(	(	PUNCT
fcis-11957	55	33	220905181091456	220905181091456	NUM
fcis-11957	55	34	)	)	PUNCT
fcis-11957	55	35	.	.	PUNCT
fcis-11957	56	1	references	reference	NOUN
fcis-11957	56	2	[	[	X
fcis-11957	56	3	1	1	X
fcis-11957	56	4	]	]	X
fcis-11957	56	5	wenjia	wenjia	X
fcis-11957	56	6	l	l	NOUN
fcis-11957	56	7	,	,	PUNCT
fcis-11957	56	8	xiaofeng	xiaofeng	PROPN
fcis-11957	56	9	z	z	PROPN
fcis-11957	56	10	,	,	PUNCT
fcis-11957	56	11	lian	lian	PROPN
fcis-11957	56	12	z.	z.	PROPN
fcis-11957	56	13	business	business	PROPN
fcis-11957	56	14	process	process	NOUN
fcis-11957	56	15	clustering	cluster	VERB
fcis-11957	56	16	method	method	NOUN
fcis-11957	56	17	based	base	VERB
fcis-11957	56	18	on	on	ADP
fcis-11957	56	19	k	k	NOUN
fcis-11957	56	20	-	-	PUNCT
fcis-11957	56	21	means	means	NOUN
fcis-11957	56	22	and	and	CCONJ
fcis-11957	56	23	elbow	elbow	VERB
fcis-11957	56	24	method[j	method[j	PROPN
fcis-11957	56	25	]	]	PUNCT
fcis-11957	56	26	.	.	PUNCT
fcis-11957	57	1	j.	j.	PROPN
fcis-11957	57	2	jianghan	jianghan	PROPN
fcis-11957	57	3	univ	univ	PROPN
fcis-11957	57	4	,	,	PUNCT
fcis-11957	57	5	2020	2020	NUM
fcis-11957	57	6	,	,	PUNCT
fcis-11957	57	7	48	48	NUM
fcis-11957	57	8	:	:	SYM
fcis-11957	57	9	81	81	NUM
fcis-11957	57	10	-	-	SYM
fcis-11957	57	11	90	90	NUM
fcis-11957	57	12	.	.	PUNCT
fcis-11957	58	1	[	[	X
fcis-11957	58	2	2	2	X
fcis-11957	58	3	]	]	PUNCT
fcis-11957	58	4	zheng	zheng	PROPN
fcis-11957	58	5	min	min	PROPN
fcis-11957	58	6	,	,	PUNCT
fcis-11957	58	7	zhang	zhang	PROPN
fcis-11957	58	8	yuzheng	yuzheng	PROPN
fcis-11957	58	9	,	,	PUNCT
fcis-11957	58	10	lv	lv	PROPN
fcis-11957	58	11	haiyong	haiyong	PROPN
fcis-11957	58	12	,	,	PUNCT
fcis-11957	58	13	et	et	PROPN
fcis-11957	58	14	al	al	PROPN
fcis-11957	58	15	.	.	PROPN
fcis-11957	58	16	stata	stata	PROPN
fcis-11957	58	17	implementation	implementation	NOUN
fcis-11957	58	18	method	method	NOUN
fcis-11957	58	19	of	of	ADP
fcis-11957	58	20	dichotomous	dichotomous	ADJ
fcis-11957	58	21	outcome	outcome	NOUN
fcis-11957	58	22	clinical	clinical	ADJ
fcis-11957	58	23	prediction	prediction	NOUN
fcis-11957	58	24	model	model	NOUN
fcis-11957	58	25	based	base	VERB
fcis-11957	58	26	on	on	ADP
fcis-11957	58	27	logistic	logistic	ADJ
fcis-11957	58	28	regression	regression	NOUN
fcis-11957	58	29	[	[	X
fcis-11957	58	30	china	china	PROPN
fcis-11957	58	31	health	health	PROPN
fcis-11957	58	32	statistics	statistic	NOUN
fcis-11957	58	33	,	,	PUNCT
fcis-11957	58	34	2022,39(03):461	2022,39(03):461	NUM
fcis-11957	58	35	-	-	SYM
fcis-11957	58	36	464	464	NUM
fcis-11957	58	37	.	.	PUNCT
fcis-11957	59	1	[	[	X
fcis-11957	59	2	3	3	X
fcis-11957	59	3	]	]	X
fcis-11957	59	4	lu	lu	NOUN
fcis-11957	59	5	shan	shan	PROPN
fcis-11957	59	6	.	.	PUNCT
fcis-11957	60	1	research	research	NOUN
fcis-11957	60	2	on	on	ADP
fcis-11957	60	3	influencing	influence	VERB
fcis-11957	60	4	factors	factor	NOUN
fcis-11957	60	5	of	of	ADP
fcis-11957	60	6	rural	rural	ADJ
fcis-11957	60	7	revitalization	revitalization	NOUN
fcis-11957	60	8	based	base	VERB
fcis-11957	60	9	on	on	ADP
fcis-11957	60	10	binary	binary	ADJ
fcis-11957	60	11	logistic	logistic	ADJ
fcis-11957	60	12	regression	regression	NOUN
fcis-11957	60	13	model	model	NOUN
fcis-11957	60	14	:	:	PUNCT
fcis-11957	60	15	from	from	ADP
fcis-11957	60	16	the	the	DET
fcis-11957	60	17	perspective	perspective	NOUN
fcis-11957	60	18	of	of	ADP
fcis-11957	60	19	grassroots	grassroot	NOUN
fcis-11957	60	20	cadre	cadre	NOUN
fcis-11957	60	21	contemporary	contemporary	ADJ
fcis-11957	60	22	economy	economy	NOUN
fcis-11957	60	23	,	,	PUNCT
fcis-11957	60	24	2022	2022	NUM
fcis-11957	60	25	,	,	PUNCT
fcis-11957	60	26	39	39	NUM
fcis-11957	60	27	(	(	PUNCT
fcis-11957	60	28	07):106	07):106	NOUN
fcis-11957	60	29	-	-	SYM
fcis-11957	60	30	110	110	NUM
fcis-11957	60	31	.	.	PUNCT