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t
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5
Wi
th
t
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in
c
re
a
sin
g
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o
f
we
b
-
b
a
se
d
to
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ls
fo
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tex
t
a
n
a
ly
sis,
t
h
e
re
is
a
g
ro
wi
n
g
re
li
a
n
c
e
o
n
a
u
to
m
a
ted
s
y
ste
m
s
to
a
ss
e
ss
tex
t
d
iffi
c
u
lt
y
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n
d
c
las
sify
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ts
to
t
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m
m
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ro
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e
a
n
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ra
m
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f
Re
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n
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e
fo
r
Lan
g
u
a
g
e
s
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R).
Ho
we
v
e
r,
i
n
c
o
n
siste
n
c
i
e
s
in
t
h
e
se
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u
tp
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ts
c
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l
d
u
n
d
e
rm
i
n
e
th
e
ir
e
ffe
c
ti
v
e
n
e
ss
fo
r
lan
g
u
a
g
e
lea
rn
e
rs
a
n
d
re
se
a
rc
h
e
rs.
T
h
is
stu
d
y
in
v
e
stig
a
tes
th
e
c
o
n
siste
n
c
y
o
f
f
i
v
e
wid
e
l
y
u
se
d
a
u
to
m
a
ted
CEF
R
a
n
a
ly
z
e
r
to
o
ls,
i
n
c
lu
d
in
g
Ch
a
tG
P
T,
b
y
a
n
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ly
z
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g
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0
En
g
li
sh
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e
sc
rip
ti
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e
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ts
a
t
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lev
e
ls
B1
a
n
d
B
2
.
A
q
u
a
n
t
it
a
ti
v
e
a
p
p
r
o
a
c
h
wa
s
e
m
p
lo
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e
d
t
o
c
o
m
p
a
re
th
e
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c
las
sifica
ti
o
n
s
g
e
n
e
ra
ted
b
y
t
h
e
se
to
o
ls
.
Th
e
re
su
l
ts
re
v
e
a
l
sig
n
ifi
c
a
n
t
in
c
o
n
siste
n
c
ies
a
c
ro
s
s
th
e
t
o
o
ls,
ra
isin
g
c
o
n
c
e
rn
s
a
b
o
u
t
t
h
e
re
li
a
b
il
it
y
o
f
a
u
t
o
m
a
ted
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R
a
li
g
n
m
e
n
t.
Ad
d
it
io
n
a
ll
y
,
t
h
e
c
o
n
ten
t
a
n
d
g
e
n
re
o
f
tex
ts
a
p
p
e
a
re
d
to
i
n
flu
e
n
c
e
th
e
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R
c
las
sifica
ti
o
n
,
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g
g
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g
t
h
a
t
c
e
rta
in
fa
c
to
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e
y
o
n
d
t
h
e
to
o
ls
’
a
lg
o
rit
h
m
s
m
a
y
a
ffe
c
t
th
e
ir
a
c
c
u
ra
c
y
.
T
h
e
se
fin
d
i
n
g
s
h
a
v
e
imp
o
r
tan
t
imp
li
c
a
ti
o
n
s
f
o
r
lan
g
u
a
g
e
e
d
u
c
a
to
rs,
c
u
rricu
l
u
m
d
e
sig
n
e
rs,
a
n
d
re
se
a
rc
h
e
rs
wh
o
re
ly
o
n
a
u
t
o
m
a
ted
CEF
R
to
o
l
s
fo
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tex
t
se
lec
ti
o
n
,
g
ra
d
in
g
,
a
n
d
a
n
a
ly
sis.
Th
e
stu
d
y
h
i
g
h
li
g
h
ts
th
e
li
m
it
a
ti
o
n
s
o
f
a
u
to
m
a
ted
CE
F
R
c
las
sifica
ti
o
n
sy
ste
m
s
a
n
d
c
a
ll
s
f
o
r
a
m
o
re
q
u
a
li
tati
v
e
a
p
p
ro
a
c
h
to
tex
t
d
iffi
c
u
lt
y
a
li
g
n
m
e
n
t
a
n
a
ly
sis.
F
u
tu
re
re
se
a
rc
h
re
c
o
m
m
e
n
d
a
ti
o
n
is
d
isc
u
ss
e
d
a
n
d
c
a
ll
fo
r
m
o
re
fo
c
u
s
o
n
re
fin
i
n
g
t
h
e
se
to
o
ls
a
n
d
e
x
p
l
o
ri
n
g
a
d
d
it
i
o
n
a
l
fa
c
to
rs
th
a
t
m
a
y
imp
a
c
t
th
e
ir
e
ffe
c
ti
v
e
n
e
ss
in
tex
t
d
iffi
c
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lt
y
m
e
a
su
re
m
e
n
t
a
n
d
C
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R
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li
g
n
m
e
n
t
.
K
ey
w
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r
d
s
:
An
aly
ze
r
to
o
ls
Au
to
m
ated
tex
t a
n
al
y
s
is
C
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T
ex
t d
if
f
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lty
class
if
icatio
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W
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ased
an
aly
s
is
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s
a
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rticle
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d
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r th
e
CC B
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C
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r
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s
p
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A
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r
:
Ap
h
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g
-
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ts
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a
Facu
lty
o
f
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ib
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A
r
ts
,
Ma
h
id
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l U
n
iv
er
s
ity
9
9
9
4
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Mo
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Ph
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Dis
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Pat
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7
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T
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ail: a
p
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m
ah
id
o
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1.
I
NT
RO
D
UCT
I
O
N
T
h
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p
u
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f
th
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ex
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tex
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d
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t
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t
o
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E
n
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tex
t
d
if
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icu
lty
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as
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o
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ies,
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eg
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n
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with
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a
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2
0
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t
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u
ch
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Gu
n
n
i
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g
-
Fo
x
I
n
d
ex
[
1
]
,
[
2
]
.
T
h
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f
o
r
m
u
las
p
r
im
ar
ily
r
ely
o
n
q
u
an
titativ
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ca
lcu
latio
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s
o
f
lin
g
u
is
tic
f
ea
tu
r
es,
in
clu
d
i
n
g
s
y
n
tactic
an
d
s
em
a
n
tic
co
m
p
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x
ity
,
v
o
ca
b
u
lar
y
f
am
iliar
ity
,
s
y
llab
le
co
u
n
ts
,
a
n
d
th
e
n
u
m
b
er
o
f
wo
r
d
s
p
er
s
en
ten
ce
.
W
h
ile
th
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ab
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f
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r
m
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las
h
av
e
b
ee
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ex
ten
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o
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s
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ap
e
p
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p
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o
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if
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[
3
]
,
[
4
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.
Ad
v
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ts
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s
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(
NL
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m
p
u
tatio
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tics
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s
ig
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ican
tly
im
p
r
o
v
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th
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class
ic
r
ea
d
ab
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f
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r
m
u
las,
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tr
o
d
u
ci
n
g
in
n
o
v
ativ
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tech
n
iq
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d
m
o
d
els
f
o
r
tex
t
d
if
f
icu
lty
an
aly
s
is
[
4
]
.
Fo
r
in
s
tan
ce
,
th
eo
r
ies
o
f
tex
t
co
m
p
r
eh
e
n
s
io
n
h
av
e
b
e
en
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teg
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ated
in
to
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las,
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ch
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th
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s
e
in
tr
o
d
u
ce
d
b
y
C
r
o
s
s
ley
et
a
l
.
[
4
]
,
wh
ic
h
em
p
l
o
y
a
d
v
a
n
ce
d
NL
P
to
o
ls
to
p
r
o
d
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ce
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o
r
e
p
r
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l
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o
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et
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d
s
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As
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esu
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au
t
o
m
ated
o
n
lin
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in
s
tr
u
m
e
n
ts
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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2252
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8
8
2
2
I
n
t
J
E
v
al
&
R
es E
d
u
c
,
Vo
l
.
14
,
No
.
4
,
Au
g
u
s
t
20
25
:
3
2
8
3
-
3
2
9
4
3284
ha
v
e
b
ec
o
m
e
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n
cr
ea
s
in
g
ly
ac
c
ess
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le
to
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u
ag
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teac
h
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s
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tex
t
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r
s
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d
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s
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ab
lin
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ass
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tex
t d
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lty
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icien
tly
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Alth
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g
h
u
s
er
s
m
ay
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av
e
v
ar
y
in
g
cr
iter
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f
o
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tin
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ese
to
o
ls
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th
ey
s
h
ar
e
a
co
m
m
o
n
p
u
r
p
o
s
e:
b
en
ch
m
ar
k
in
g
tex
t
s
to
ap
p
r
o
p
r
iate
d
if
f
icu
lty
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els
to
in
f
o
r
m
lan
g
u
ag
e
teac
h
in
g
,
ass
es
s
m
en
t,
an
d
s
k
ill
d
ev
elo
p
m
en
t.
T
h
is
p
r
o
ce
s
s
,
k
n
o
wn
as
m
ater
ial
lev
elin
g
,
aim
s
to
ali
g
n
tex
ts
to
s
p
ec
if
ic
d
if
f
icu
lty
lev
els f
o
r
tar
g
eted
u
s
e
[
5
]
.
T
h
e
C
o
m
m
o
n
E
u
r
o
p
ea
n
Fra
m
ewo
r
k
o
f
R
ef
er
en
ce
f
o
r
L
an
g
u
ag
es
(
C
E
FR
)
:
lear
n
in
g
,
teac
h
in
g
,
ass
es
s
m
en
t
s
er
v
es
as
a
g
u
id
e
lin
e
to
p
r
o
v
id
e
co
h
e
r
en
ce
a
n
d
s
tan
d
ar
d
izatio
n
in
m
ater
ial
lev
elin
g
.
I
n
itially
d
ev
elo
p
e
d
to
s
tan
d
ar
d
ize
tex
t
b
o
o
k
s
,
cu
r
r
ic
u
la,
a
n
d
ex
am
in
atio
n
s
in
E
u
r
o
p
e,
t
h
e
C
E
FR
f
r
am
ewo
r
k
class
if
ies
lan
g
u
ag
e
p
r
o
f
icien
cy
i
n
to
b
asic
(
A1
-
A2
)
,
in
d
ep
en
d
en
t
(
B
1
-
B
2
)
,
an
d
p
r
o
f
icien
t
(
C
1
-
C
2
)
u
s
er
s
[
6
]
.
I
ts
s
tr
aig
h
tf
o
r
war
d
d
escr
ip
to
r
s
a
n
d
clea
r
co
m
m
u
n
icativ
e
g
o
a
ls
h
av
e
f
ac
ilit
ated
its
ad
o
p
ti
o
n
wo
r
l
d
wid
e
as
a
f
o
u
n
d
atio
n
f
o
r
lan
g
u
ag
e
teac
h
in
g
an
d
ass
ess
m
en
t
[
7
]
.
E
d
u
ca
tio
n
al
in
s
titu
tio
n
s
an
d
g
o
v
er
n
m
en
t
o
r
g
an
izatio
n
s
h
a
v
e
r
ec
o
g
n
ize
d
an
d
em
b
r
ac
e
d
C
E
FR
as
a
g
u
id
elin
e
f
o
r
ex
p
ec
te
d
la
n
g
u
a
g
e
p
r
o
f
icien
c
y
o
u
tco
m
es.
Fo
r
in
s
tan
ce
,
t
h
e
C
o
m
m
is
s
io
n
o
n
Hig
h
er
E
d
u
ca
tio
n
Stan
d
ar
d
s
(
C
HE
S)
u
n
d
er
th
e
Of
f
ice
o
f
th
e
Per
m
an
en
t
Secr
etar
y
o
f
T
h
ailan
d
s
et
o
u
t
C
E
FR
p
o
licy
in
2
0
2
4
,
s
p
ec
if
y
in
g
th
at
u
n
d
er
g
r
ad
u
ate
s
tu
d
en
ts
s
h
o
u
ld
ac
h
iev
e
at
lea
s
t
B
2
p
r
o
f
ic
ien
cy
,
wh
ile
g
r
a
d
u
ate
s
tu
d
en
ts
s
h
o
u
ld
attain
C
1
b
ef
o
r
e
g
r
ad
u
atio
n
.
T
h
is
p
o
licy
h
as
d
r
iv
en
m
a
n
y
h
i
g
h
er
ed
u
c
atio
n
in
s
titu
tio
n
s
to
alig
n
th
eir
lan
g
u
a
g
e
teac
h
in
g
an
d
ass
ess
m
en
t
p
r
ac
tices
wi
th
C
E
F
R
d
escr
ip
to
r
s
[
8
]
–
[
1
0
]
.
Ho
wev
er
,
th
e
ap
p
licatio
n
o
f
C
E
FR
r
em
ain
s
ch
allen
g
in
g
f
o
r
test
d
ev
elo
p
er
s
,
m
ater
ial
c
r
ea
to
r
s
,
an
d
e
d
u
ca
to
r
s
,
as
its
d
escr
ip
to
r
s
ar
e
o
p
e
n
to
v
ar
y
in
g
in
ter
p
r
etatio
n
s
.
M
o
r
e
o
v
er
,
C
E
FR
d
o
es
n
o
t
p
r
escr
ib
e
s
p
ec
if
ic
teac
h
in
g
m
eth
o
d
o
lo
g
ies
o
r
ass
ess
m
en
ts
,
leav
in
g
ed
u
c
ato
r
s
to
ad
a
p
t a
n
d
in
teg
r
ate
its
f
r
am
ewo
r
k
in
to
t
h
eir
u
n
iq
u
e
co
n
tex
ts
.
Fo
r
ex
a
m
p
le,
C
E
FR
-
lev
eled
tex
ts
o
f
ten
r
eq
u
ir
e
m
o
d
if
icatio
n
to
s
u
it th
e
n
ee
d
s
o
f
lan
g
u
ag
e
lear
n
er
s
[
1
1
]
.
Giv
en
th
e
cr
itical
r
o
le
o
f
te
x
t
cl
ass
if
icatio
n
o
r
m
ater
ial
le
v
elin
g
in
lan
g
u
ag
e
ed
u
ca
tio
n
,
ed
u
ca
to
r
s
m
u
s
t
en
s
u
r
e
th
at
s
elec
ted
te
x
ts
alig
n
ac
c
u
r
ately
with
lea
r
n
er
s
'
p
r
o
f
icien
c
y
lev
els
[
1
2
]
.
T
h
ese
c
h
allen
g
es
h
ig
h
lig
h
t
th
e
im
p
o
r
tan
c
e
o
f
ex
p
lo
r
in
g
a
u
to
m
ated
tex
t
cla
s
s
if
icatio
n
to
o
ls
th
at
claim
to
m
ap
with
s
p
ec
if
ic
C
E
FR
d
escr
ip
to
r
s
,
as
r
eliab
le
to
o
ls
ar
e
es
s
en
tial
f
o
r
ef
f
ec
tiv
ely
s
u
p
p
o
r
tin
g
lan
g
u
a
g
e
lear
n
in
g
an
d
m
ater
ial
s
elec
tio
n
.
T
h
e
n
o
v
elty
o
f
th
is
p
ap
er
lies
i
n
its
f
o
c
u
s
o
n
th
e
r
o
le
o
f
au
to
m
ated
C
E
FR
alig
n
m
en
t
to
o
ls
at
th
e
tex
t
lev
el,
an
ar
ea
th
at
h
as
r
ec
ei
v
ed
lim
ited
atten
tio
n
co
m
p
a
r
ed
to
b
r
o
a
d
er
C
E
FR
alig
n
m
en
t
p
r
ac
tices.
B
y
u
n
co
v
e
r
in
g
th
e
v
ar
iab
ilit
y
in
C
E
FR
c
lass
if
icatio
n
s
ac
r
o
s
s
d
if
f
er
en
t
to
o
ls
,
th
e
s
tu
d
y
h
i
g
h
lig
h
ts
th
e
n
ee
d
f
o
r
ca
u
tio
n
in
em
p
lo
y
in
g
co
m
p
u
tatio
n
al
m
eth
o
d
s
,
en
s
u
r
in
g
th
ey
alig
n
with
th
e
s
p
ec
if
ic
p
u
r
p
o
s
es
o
f
C
E
FR
class
if
icatio
n
.
Fu
r
th
er
m
o
r
e,
it
em
p
h
asizes
th
e
im
p
o
r
tan
ce
o
f
in
teg
r
atin
g
h
u
m
a
n
ju
d
g
m
e
n
t
to
en
h
an
ce
th
e
r
eliab
ilit
y
o
f
tex
t
d
if
f
icu
lty
ass
es
s
m
en
ts
.
T
h
ese
f
in
d
in
g
s
p
r
o
v
id
e
v
alu
ab
le
in
s
ig
h
ts
f
o
r
ed
u
ca
to
r
s
,
p
o
licy
m
ak
er
s
,
a
n
d
d
ev
elo
p
e
r
s
s
ee
k
in
g
to
im
p
r
o
v
e
t
h
e
ef
f
ec
ti
v
en
ess
o
f
C
E
FR
alig
n
m
en
t to
o
ls
.
2.
L
I
T
E
R
AT
U
RE
R
E
VI
E
W
2
.
1
.
T
ex
t
cla
s
s
if
ica
t
io
n ba
s
ed
o
n CEFR
g
uid
el
ine
T
ex
t
class
if
icatio
n
u
n
d
er
C
E
FR
g
u
id
elin
es
h
as
g
ain
ed
in
cr
ea
s
in
g
im
p
o
r
tan
ce
in
r
ec
e
n
t
y
ea
r
s
[
1
3
]
.
E
v
alu
atin
g
an
d
s
elec
tin
g
ap
p
r
o
p
r
iate
tex
ts
r
em
ain
s
ch
all
en
g
in
g
f
o
r
lan
g
u
ag
e
teac
h
er
s
.
T
r
ad
itio
n
al
tex
t
class
if
icatio
n
ap
p
r
o
ac
h
es
o
f
te
n
r
ely
o
n
s
h
allo
w
lin
g
u
is
tic
f
e
atu
r
es,
wh
ich
d
o
n
o
t
f
u
lly
r
ef
l
ec
t
th
e
ac
tu
al
lev
el
o
f
tex
t
d
if
f
icu
lty
.
C
o
n
s
eq
u
e
n
tly
,
v
ar
io
u
s
m
eth
o
d
s
h
av
e
b
ee
n
d
ev
elo
p
ed
to
e
n
h
an
c
e
an
d
s
im
p
lify
tex
t
class
if
icatio
n
b
ased
o
n
d
if
f
ic
u
lty
lev
els.
On
lin
e
r
eso
u
r
ce
s
o
f
f
er
in
g
lim
itles
s
ac
ce
s
s
to
au
th
en
tic
tex
t
s
h
av
e
also
p
r
o
m
p
te
d
th
e
i
n
teg
r
atio
n
o
f
m
o
d
el
tex
t
r
ec
o
m
m
en
d
atio
n
s
y
s
tem
s
in
to
class
r
o
o
m
s
to
b
etter
en
g
ag
e
la
n
g
u
a
g
e
lear
n
er
s
[
1
4
]
.
R
esear
ch
b
y
E
s
co
b
ar
-
Ace
v
ed
o
et
a
l
.
[
1
4
]
s
u
g
g
ested
em
p
lo
y
in
g
au
to
m
atic
class
if
ier
s
b
ased
o
n
C
E
FR
g
u
id
elin
es
to
s
tr
ea
m
lin
e
th
e
s
elec
tio
n
o
f
tex
ts
f
r
o
m
a
u
th
en
tic
s
o
u
r
ce
s
,
s
u
c
h
as
o
n
lin
e
p
latf
o
r
m
s
[
1
4
]
.
Ho
wev
er
,
attem
p
ts
to
cl
ass
if
y
tex
ts
u
s
in
g
au
to
m
ated
to
o
ls
h
av
e
o
f
ten
y
ield
e
d
in
co
n
s
is
ten
t r
esu
lts
[
1
5
]
.
R
ec
en
t
ad
v
an
ce
m
e
n
ts
in
clu
d
e
th
e
u
s
e
o
f
m
ac
h
in
e
lear
n
i
n
g
tech
n
iq
u
es
s
u
c
h
as
th
e
b
id
ir
ec
tio
n
al
en
co
d
er
r
ep
r
esen
tatio
n
s
f
r
o
m
tr
an
s
f
o
r
m
e
r
s
(
B
E
R
T
)
m
o
d
el
f
o
r
C
E
FR
tex
t
class
if
icatio
n
[
1
3
]
.
Stu
d
ies
d
em
o
n
s
tr
ate
th
at
a
u
to
m
ated
tex
t
-
lev
el
d
etec
tio
n
is
ef
f
ec
tiv
e,
with
th
e
q
u
ality
o
f
cla
s
s
if
icatio
n
lar
g
ely
d
ep
en
d
e
n
t
o
n
th
e
tex
t
co
r
p
u
s
u
s
ed
.
Fo
r
in
s
tan
ce
,
Sch
m
alz
an
d
B
r
u
tti
[
1
6
]
p
r
o
p
o
s
ed
an
alter
n
ativ
e
ap
p
r
o
ac
h
u
s
in
g
a
B
E
R
T
-
b
ased
m
o
d
el,
r
ep
o
r
tin
g
s
u
cc
ess
in
au
to
m
ate
d
C
E
FR
tex
t
class
i
f
icatio
n
s
u
p
p
o
r
ted
b
y
s
ig
n
if
ica
n
t
n
u
m
er
ical
d
ata
[
1
6
]
.
Ho
we
v
e
r
,
th
e
p
r
ac
tical
ap
p
licatio
n
o
f
th
ese
m
o
d
els
in
la
n
g
u
a
g
e
cl
ass
r
o
o
m
s
r
em
ain
s
ch
allen
g
in
g
.
B
E
R
T
-
b
ased
s
y
s
tem
s
r
eq
u
ir
e
e
x
ten
s
iv
e
m
an
u
al
d
ata
lab
elin
g
f
o
r
tr
ain
in
g
,
as
th
e
p
r
e
-
t
r
ain
ed
m
o
d
el
is
b
ased
o
n
p
lain
te
x
t
f
r
o
m
s
o
u
r
ce
s
lik
e
t
h
e
E
n
g
lis
h
W
ik
ip
ed
ia
an
d
th
e
B
r
o
wn
C
o
r
p
u
s
.
T
h
is
p
r
o
ce
s
s
is
lab
o
r
-
in
ten
s
iv
e
a
n
d
m
a
y
b
e
im
p
r
ac
tical
f
o
r
teac
h
er
s
with
v
ar
y
in
g
lev
els o
f
tech
n
ical
liter
ac
y
[
1
7
]
.
Oth
er
s
tu
d
ies
p
r
o
p
o
s
e
co
m
b
i
n
in
g
q
u
an
titativ
e
an
d
q
u
alita
tiv
e
ap
p
r
o
ac
h
es
f
o
r
tex
t
class
if
icatio
n
u
n
d
er
C
E
FR
g
u
id
elin
es.
Nat
o
v
a
[
1
5
]
in
tr
o
d
u
ce
d
th
r
ee
q
u
an
titativ
e
to
o
ls
:
i)
T
h
e
L
ex
ile
f
r
am
ewo
r
k
f
o
r
r
ea
d
in
g
;
ii)
T
h
e
Fles
ch
r
ea
d
in
g
ea
s
e
in
d
ex
;
an
d
iii)
T
h
e
l
ex
ical
p
r
o
f
iler
in
T
ex
t
I
n
s
p
ec
to
r
.
Fo
r
q
u
alitativ
e
ass
es
s
m
en
t,
m
an
u
al
a
n
aly
s
is
in
co
r
p
o
r
atin
g
h
u
m
an
ju
d
g
m
en
t
o
f
tex
t
m
ea
n
in
g
,
s
tr
u
ctu
r
e,
g
r
am
m
atica
l
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J
E
v
al
&
R
es E
d
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c
I
SS
N:
2252
-
8
8
2
2
E
va
lu
a
tin
g
t
h
e
co
n
s
is
ten
cy
o
f
a
u
to
ma
ted
C
E
F
R
a
n
a
lyzer
s
:
a
s
tu
d
y
o
f E
n
g
lis
h
…
(
P
iya
th
a
t
S
ir
ip
o
l
)
3285
co
m
p
lex
ity
,
an
d
co
g
n
itiv
e
d
e
m
an
d
was
em
p
lo
y
ed
.
W
h
ile
Nato
v
as
f
in
d
in
g
s
[
1
5
]
in
d
icat
e
th
at
s
u
ch
to
o
ls
h
o
ld
p
o
ten
tial,
th
e
class
if
ica
tio
n
l
ev
els
h
ea
v
ily
ap
p
ea
r
ed
to
b
e
in
f
lu
en
ce
d
b
y
q
u
alitativ
e
cr
iter
ia.
T
h
is
r
aises
q
u
esti
o
n
s
ab
o
u
t
t
h
e
co
n
s
is
ten
c
y
an
d
p
r
ec
is
io
n
o
f
au
to
m
ated
to
o
ls
in
lev
elin
g
o
r
b
e
n
ch
m
a
r
k
in
g
tex
ts
to
C
E
FR
lev
els.
Qu
an
titativ
e
as
s
ess
m
e
n
ts
,
as
s
h
o
wn
b
y
Nato
v
a
[
1
5
]
,
illu
s
tr
ate
th
e
v
ar
iab
ilit
y
o
f
C
E
FR
cla
s
s
if
icatio
n
s
ac
r
o
s
s
d
if
f
er
e
n
t
au
to
m
ated
to
o
ls
,
p
o
ten
tially
lead
in
g
to
in
ac
cu
r
ate
in
ter
p
r
etatio
n
s
o
f
tex
t
d
if
f
ic
u
lty
.
T
h
e
in
co
n
s
is
ten
cy
s
tem
s
f
r
o
m
th
e
v
ar
y
in
g
f
r
am
ewo
r
k
s
an
d
alg
o
r
ith
m
s
u
n
d
e
r
ly
in
g
th
ese
t
o
o
ls
,
n
ec
ess
itatin
g
fu
r
th
er
ex
p
lo
r
atio
n
.
T
h
is
g
ap
in
th
e
liter
atu
r
e
h
ig
h
lig
h
ts
co
n
ce
r
n
s
f
o
r
ed
u
ca
to
r
s
,
m
ater
ial
d
ev
elo
p
er
s
,
an
d
tex
t
wr
iter
s
[
1
8
]
.
2
.
2
.
Aut
o
m
a
t
ed
CE
F
R
t
ex
t
cl
a
s
s
i
f
ica
t
io
n t
o
o
ls
C
u
r
r
en
tly
,
n
u
m
er
o
u
s
au
to
m
a
ted
to
o
ls
ar
e
av
ailab
le
f
o
r
teac
h
er
s
an
d
m
ate
r
ial
d
ev
elo
p
er
s
to
b
en
ch
m
ar
k
tex
t
d
if
f
icu
lty
ag
a
in
s
t
C
E
F
R
lev
els.
T
h
ese
to
o
ls
f
ac
ilit
ate
q
u
ick
a
n
aly
s
is
an
d
p
r
o
v
id
e
r
esu
lts
th
at
g
u
id
e
m
ater
ial
d
ev
elo
p
m
en
t
a
n
d
class
r
o
o
m
p
r
ac
tices.
Sev
e
r
al
to
o
ls
,
s
u
ch
as
C
ath
o
v
en
AI
,
T
ex
t
I
n
s
p
ec
to
r
,
an
d
Pear
s
o
n
’
s
Glo
b
al
Scale
o
f
E
n
g
lis
h
(
GSE)
,
ar
e
wid
ely
u
tili
ze
d
as v
alid
atio
n
to
o
ls
in
lan
g
u
ag
e
r
esear
ch
.
2
.
2
.
1
.
Ca
t
ho
v
en
AI
C
ath
o
v
en
AI
’
s
C
E
FR
C
h
ec
k
e
r
ev
alu
ates
tex
ts
b
y
an
aly
zin
g
lin
g
u
is
tic
f
ac
to
r
s
s
u
ch
a
s
v
o
ca
b
u
lar
y
,
g
r
am
m
ar
,
s
en
ten
ce
s
tr
u
ct
u
r
e,
an
d
p
h
r
ases
.
A
u
n
iq
u
e
f
ea
tu
r
e
is
its
ab
ili
ty
to
p
r
o
v
id
e
d
ec
i
m
al
-
lev
el
p
r
ec
is
io
n
f
o
r
C
E
FR
class
if
icat
io
n
s
.
Fo
r
in
s
tan
ce
,
a
tex
t
m
ig
h
t
b
e
class
if
ied
as
A2
.
7
,
in
d
icatin
g
it
is
clo
s
e
to
B
1
.
Ho
wev
er
,
th
e
to
o
l
d
o
es
n
o
t
p
r
o
v
id
e
alg
o
r
ith
m
ic
tr
an
s
p
a
r
e
n
cy
in
ex
p
lain
in
g
h
o
w
th
ese
d
ec
im
al
v
alu
es
ar
e
d
er
iv
ed
an
d
m
ay
leav
e
u
s
er
s
with
o
u
t
in
s
ig
h
t
in
to
th
e
u
n
d
e
r
ly
in
g
alg
o
r
ith
m
s
.
Desp
ite
th
is
l
im
itatio
n
,
C
ath
o
v
en
AI
allo
ws
u
s
er
s
to
ex
p
lo
r
e
d
etailed
C
E
FR
r
ep
o
r
ts
f
o
r
v
o
ca
b
u
lar
y
,
te
n
s
e
,
clau
s
e,
an
d
s
en
ten
ce
-
lev
el
class
if
icatio
n
s
.
Stu
d
ies
h
av
e
em
p
lo
y
ed
C
ath
o
v
en
AI
f
o
r
t
ex
t
d
if
f
icu
lty
an
aly
s
is
an
d
C
E
FR
b
en
ch
m
ar
k
i
n
g
,
h
ig
h
lig
h
tin
g
its
p
o
ten
tial a
p
p
li
ca
tio
n
s
[
1
9
]
,
[
2
0
]
.
2
.
2
.
2
.
G
lo
ba
l Sca
le
o
f
E
ng
lis
h
GSE
p
r
o
v
i
d
es
a
g
r
an
u
lar
p
r
o
f
i
cien
cy
s
ca
le
f
r
o
m
1
0
to
9
0
,
al
ig
n
in
g
with
C
E
FR
lev
els.
I
n
it
ially
u
s
ed
f
o
r
t
h
e
Pear
s
o
n
T
est
o
f
E
n
g
lis
h
Aca
d
em
ic
(
PTE
Aca
d
e
m
ic)
,
it
was
later
v
alid
ated
a
g
ain
s
t
s
tan
d
ar
d
ized
test
s
s
u
ch
as
in
ter
n
atio
n
al
E
n
g
lis
h
lan
g
u
ag
e
test
in
g
s
y
s
tem
o
r
I
E
L
T
S
an
d
test
o
f
E
n
g
lis
h
as
a
f
o
r
eig
n
la
n
g
u
a
g
e
o
r
T
OE
FL.
T
h
e
GSE
to
o
lk
it
o
f
f
er
s
f
ea
tu
r
es
f
o
r
te
x
t
an
aly
s
is
,
in
clu
d
in
g
C
E
FR
eq
u
iv
alen
cy
p
o
in
ts
,
r
ea
d
a
b
ilit
y
m
ea
s
u
r
es
(
e.
g
.
,
AR
I
,
Fles
ch
-
Kin
ca
id
,
an
d
SMOG)
,
a
n
d
h
ig
h
lig
h
ted
v
o
ca
b
u
lar
y
e
x
ce
ed
in
g
cu
r
r
en
t
C
E
FR
lev
els.
T
h
is
to
o
l
h
as
b
ee
n
p
a
r
ticu
lar
ly
ef
f
ec
tiv
e
f
o
r
ass
ess
in
g
tex
t
d
if
f
icu
lty
with
co
n
s
is
ten
cy
an
d
f
in
e
-
g
r
ain
ed
in
s
ig
h
ts
in
to
p
r
o
f
icie
n
cy
lev
el
s
.
2
.
2
.
3
.
T
ex
t
I
ns
pect
o
r
T
e
x
t
I
n
s
p
e
c
t
o
r
i
s
a
we
b
-
b
a
s
e
d
t
o
o
l
t
h
a
t
e
m
p
l
o
y
s
a
c
o
r
p
u
s
-
b
a
s
e
d
a
p
p
r
o
a
c
h
,
u
t
i
l
i
zi
n
g
r
e
s
o
u
r
c
es
s
u
c
h
as
t
h
e
E
n
g
l
i
s
h
V
o
c
a
b
u
l
a
r
y
P
r
o
f
i
le
(
E
V
P
)
,
A
c
a
d
e
m
i
c
W
o
r
d
L
i
s
t,
a
n
d
B
r
it
i
s
h
N
a
ti
o
n
a
l
C
o
r
p
u
s
(
B
NC
)
.
I
t
ca
l
c
u
l
at
e
s
m
e
t
r
i
c
s
l
i
k
e
t
y
p
e
-
t
o
k
e
n
r
a
t
i
o
,
s
e
n
t
e
n
c
e
l
e
n
g
t
h
,
a
n
d
s
y
l
la
b
l
e
c
o
u
n
t
t
o
d
e
t
e
r
m
i
n
e
t
e
x
t
d
i
f
f
i
c
u
l
t
y
.
A
n
o
t
a
b
l
e
f
e
a
t
u
r
e
i
s
i
ts
L
e
x
ic
a
l
P
r
o
f
i
l
e
,
w
h
i
c
h
ag
g
r
e
g
a
t
e
s
v
a
r
i
o
u
s
m
et
r
i
cs
t
o
a
s
s
i
g
n
a
C
E
F
R
l
e
v
el
.
De
s
p
it
e
i
ts
c
o
m
p
r
e
h
e
n
s
i
v
e
c
a
p
a
b
i
l
i
ti
e
s
,
t
h
e
r
e
li
a
b
i
l
it
y
o
f
r
e
s
u
l
ts
d
e
p
e
n
d
s
o
n
t
h
e
n
u
m
b
e
r
a
n
d
c
o
m
b
i
n
a
t
i
o
n
o
f
m
e
t
r
i
c
s
u
s
e
d
[
2
1
]
.
2
.
2
.
4
.
O
x
f
o
rd
T
ex
t
Check
er
Ox
f
o
r
d
T
ex
t
C
h
ec
k
er
f
o
cu
s
es
o
n
v
o
ca
b
u
la
r
y
p
r
o
f
ilin
g
b
y
e
x
am
in
in
g
tex
t
co
n
ten
t
ag
ai
n
s
t
ex
ten
s
iv
e
co
r
p
o
r
a,
in
clu
d
in
g
th
e
Ox
f
o
r
d
3
0
0
0
an
d
Ox
f
o
r
d
5
0
0
0
-
wo
r
d
lis
ts
.
Un
lik
e
o
th
er
to
o
ls
,
it
d
o
es
n
o
t
p
r
o
v
id
e
a
n
o
v
er
all
C
E
FR
lev
el
b
u
t
o
f
f
er
s
p
er
ce
n
tag
es
o
f
wo
r
d
s
co
r
r
e
s
p
o
n
d
in
g
t
o
d
if
f
e
r
en
t
C
E
FR
l
ev
els.
T
h
is
f
ea
tu
r
e
h
elp
s
u
s
er
s
esti
m
ate
th
e
p
r
o
f
i
cien
cy
lev
el
o
f
a
te
x
t,
alth
o
u
g
h
its
ap
p
licatio
n
is
lim
ited
t
o
v
o
ca
b
u
lar
y
-
b
ased
an
aly
s
es.
T
h
e
in
clu
s
io
n
o
f
wo
r
d
lis
ts
in
to
ea
ch
wo
r
d
lis
t
g
r
o
u
p
,
s
u
ch
as
Ox
f
o
r
d
3
0
0
0
,
h
as
u
n
d
er
g
o
n
e
th
r
ee
co
r
e
cr
iter
ia:
f
r
eq
u
e
n
cy
,
r
an
g
e,
an
d
f
am
iliar
ity
.
T
h
e
d
etails ar
e
s
u
m
m
ar
ized
in
T
a
b
le
1
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ab
le
1
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m
m
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l
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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2252
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8
8
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2
I
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J
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v
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Vo
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14
,
No
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4
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Au
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u
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20
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3
2
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4
3286
Ox
f
o
r
d
T
ex
t
C
h
ec
k
er
h
ig
h
lig
h
ts
wo
r
d
s
th
at
ar
e
f
r
o
m
d
i
f
f
er
en
t
lev
els
o
f
C
E
FR
.
W
ith
th
e
GSE
to
o
lk
it
,
wo
r
d
s
ar
e
n
o
t
c
o
lo
r
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FR
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p
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ce
n
tag
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o
f
wo
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d
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th
at
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t
f
r
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t
h
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iew
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ra
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ar
(
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ex
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in
Asi
an
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u
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ies.
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h
e
web
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ite
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f
f
er
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E
SL
m
ater
ials
,
g
am
es,
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u
izze
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d
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r
c
es
f
o
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SL
teac
h
er
s
.
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o
n
lin
e
to
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l
ca
lled
‘
tex
t
an
aly
ze
r
’
(
h
ttp
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r
o
ad
to
g
r
am
m
ar
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c
o
m
/tex
tan
aly
s
is
/
)
is
also
av
ailab
le
f
o
r
E
SL
t
ea
ch
er
s
to
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s
e
to
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eter
m
in
e
th
e
a
p
p
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r
iate
lev
el
o
f
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t
d
if
f
icu
lty
f
o
r
d
if
f
er
e
n
t
lev
els
o
f
s
tu
d
en
ts
’
p
r
o
f
icie
n
cy
ac
co
r
d
in
g
t
o
th
e
C
E
FR
.
T
h
e
d
etail
o
f
th
e
to
o
l,
h
o
wev
er
,
is
q
u
ite
lim
ited
co
m
p
ar
e
d
to
o
th
er
tex
t
a
n
aly
ze
r
in
s
tr
u
m
en
ts
,
ex
p
lain
in
g
b
r
ief
ly
th
at
th
e
a
n
aly
ze
r
f
o
c
u
s
es
o
n
th
e
co
m
p
lex
ity
o
f
lan
g
u
a
g
e.
T
h
e
s
u
b
m
itted
tex
t
will
b
e
co
m
p
ar
ed
to
a
lis
t
o
f
th
e
1
0
,
0
0
0
m
o
s
t
u
s
ed
wo
r
d
s
i
n
E
n
g
l
is
h
to
g
eth
er
with
th
e
p
o
s
itio
n
o
n
th
e
lis
t
an
d
th
e
a
v
er
ag
e
wo
r
d
a
n
d
s
en
ten
ce
len
g
th
.
T
h
e
web
p
a
g
e
d
o
es n
o
t c
o
n
tain
th
e
ty
p
e
o
f
co
r
p
u
s
u
s
ed
o
r
a
r
ef
er
en
ce
as to
wh
ich
wo
r
d
lis
t
is
a
r
ef
er
e
n
c
e
p
o
in
t.
W
ith
an
ea
s
y
-
to
-
u
s
e
in
ter
f
ac
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h
o
wev
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s
er
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ca
n
in
s
er
t
a
tex
t
an
d
s
im
p
ly
g
et
a
r
atin
g
o
f
th
e
C
E
FR
A2
to
C
2
.
2
.
2
.
6
.
Cha
t
G
P
T
C
h
atGPT
,
a
s
o
p
h
is
ticated
lan
g
u
ag
e
m
o
d
el
d
ev
elo
p
e
d
b
y
Op
e
n
AI
,
h
as
also
b
ee
n
u
s
ed
to
cla
s
s
if
y
tex
ts
b
y
C
E
FR
lev
el.
L
ev
er
ag
in
g
ad
v
an
ce
d
NL
P
tech
n
iq
u
es,
C
h
atGPT
ev
alu
ates
lin
g
u
is
tic
f
ea
tu
r
es
lik
e
v
o
ca
b
u
lar
y
s
o
p
h
is
ticatio
n
,
g
r
am
m
atica
l
co
m
p
lex
ity
,
an
d
s
en
ten
ce
s
tr
u
c
tu
r
e.
Un
lik
e
tr
ad
itio
n
al
to
o
ls
,
it
u
s
es
tr
an
s
f
o
r
m
er
-
b
ased
ar
ch
itectu
r
es
tr
ain
ed
o
n
d
iv
er
s
e
m
u
ltil
in
g
u
al
co
r
p
o
r
a,
en
ab
lin
g
it
to
p
r
o
v
id
e
n
u
a
n
ce
d
ass
ess
m
en
ts
.
C
h
atGPT
’
s
in
clu
s
io
n
in
th
is
s
tu
d
y
h
ig
h
lig
h
ts
th
e
p
o
ten
tial
o
f
NL
P
-
b
ased
to
o
ls
to
co
m
p
lem
en
t
tr
ad
itio
n
al
m
eth
o
d
s
.
W
h
ile
ex
is
tin
g
au
to
m
ated
to
o
ls
ar
e
wid
ely
u
s
ed
,
th
er
e
i
s
lim
ited
r
esear
ch
th
at
ex
am
in
es
th
eir
co
n
s
is
ten
cy
in
g
en
er
atin
g
C
E
FR
cla
s
s
if
icatio
n
s
.
Dif
f
er
en
ce
s
in
alg
o
r
ith
m
s
an
d
f
r
am
ewo
r
k
s
m
ay
r
esu
lt
in
v
ar
iab
le
o
u
tp
u
ts
,
p
o
s
in
g
ch
all
en
g
es
f
o
r
ed
u
ca
t
o
r
s
an
d
r
esear
ch
er
s
.
Fo
r
in
s
tan
ce
,
to
o
ls
lik
e
T
ex
t
I
n
s
p
ec
to
r
r
ely
o
n
lex
ical
p
r
o
f
ilin
g
,
wh
ile
C
h
atGPT
em
p
lo
y
s
ad
v
an
ce
d
m
a
ch
in
e
-
lear
n
in
g
tech
n
i
q
u
es.
T
h
is
s
tu
d
y
ad
d
r
ess
es
co
n
ce
r
n
s
a
b
o
u
t
w
h
eth
er
c
u
r
r
e
n
t
C
E
FR
an
aly
ze
r
p
r
o
g
r
am
s
p
r
o
v
id
e
co
n
s
is
ten
t
r
esu
lts
wh
en
class
if
y
in
g
lev
eled
tex
ts
,
aim
in
g
to
in
f
o
r
m
th
ei
r
ef
f
ec
tiv
e
u
s
e
in
lan
g
u
ag
e
teac
h
i
n
g
an
d
ass
ess
m
en
t.
3.
M
E
T
H
O
D
T
h
e
cu
r
r
e
n
t stu
d
y
e
m
p
lo
y
e
d
a
q
u
an
titativ
e
d
ata
an
al
y
s
is
ap
p
r
o
ac
h
b
y
id
en
tify
i
n
g
co
n
g
r
u
en
c
e
ac
r
o
s
s
tex
t a
n
aly
ze
r
to
o
ls
.
E
ac
h
to
o
l
was d
esig
n
ed
s
p
ec
if
ically
f
o
r
lan
g
u
ag
e
an
aly
s
is
p
u
r
p
o
s
es.
Deta
ils
o
f
th
e
s
am
p
le
tex
ts
an
d
d
ata
an
aly
s
is
ar
e
p
r
o
v
id
ed
in
t
h
e
f
o
llo
win
g
s
ec
tio
n
s
.
3
.
1
.
Sa
m
ple t
ex
t
s
a
nd
t
ex
t
s
re
cr
u
it
m
ent
T
h
is
s
tu
d
y
in
clu
d
es 2
0
tex
t sam
p
les f
r
o
m
h
ttp
s
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in
g
u
a.
co
m
th
at
o
f
f
er
r
ea
d
in
g
tex
ts
o
f
v
ar
io
u
s
C
E
FR
lev
els
in
m
o
r
e
th
an
ten
lan
g
u
ag
es,
in
clu
d
in
g
E
n
g
lis
h
.
T
h
e
web
s
ite
was
ch
o
s
en
as
it
claim
s
to
o
f
f
er
au
th
en
tic
r
ea
d
in
g
m
ater
ials
d
esig
n
ed
b
y
ex
p
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ce
d
E
n
g
lis
h
ed
u
ca
to
r
s
to
s
u
p
p
o
r
t
v
o
ca
b
u
lar
y
r
ec
o
g
n
itio
n
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d
v
ar
iatio
n
o
f
s
en
ten
ce
s
tr
u
ctu
r
e
r
ef
lecte
d
b
y
d
if
f
icu
lty
lev
els (
n
o
v
ice,
in
ter
m
ed
iate,
an
d
ad
v
an
ce
d
)
.
C
E
FR
o
f
A1
to
C
1
is
u
s
ed
to
in
d
icate
th
e
d
if
f
icu
lty
lev
els
o
f
b
asic
u
s
er
s
,
in
d
ep
en
d
en
t
u
s
er
s
,
an
d
p
r
o
f
icien
t
u
s
er
s
.
On
L
in
g
u
a.
co
m
,
r
ea
d
er
s
ca
n
ev
alu
ate
th
eir
p
r
o
g
r
ess
an
d
u
n
d
er
s
tan
d
in
g
th
r
o
u
g
h
m
u
ltip
le
-
ch
o
ice
q
u
izze
s
o
f
f
er
ed
at
th
e
en
d
o
f
r
ea
d
in
g
m
ater
ials
.
I
n
th
is
s
tu
d
y
,
t
h
e
E
n
g
l
i
s
h
l
a
n
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u
a
g
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t
e
x
t
s
w
e
r
e
c
o
l
l
e
c
t
e
d
i
n
a
g
r
o
u
p
o
f
1
0
C
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F
R
B
1
t
e
x
t
s
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n
d
1
0
C
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B
2
t
e
x
t
s
.
T
h
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r
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a
r
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2
0
f
r
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e
l
y
a
v
a
i
l
a
b
l
e
t
e
x
t
s
w
i
t
h
6
6
a
d
d
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t
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a
l
t
e
x
t
s
f
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r
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u
b
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d
m
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d
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b
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c
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m
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T
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ab
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u
b
lis
h
er
/au
th
o
r
wer
e
co
m
p
u
ted
in
to
f
iv
e
C
E
FR
tex
t
an
aly
ze
r
p
r
o
g
r
am
s
an
d
o
n
e
lar
g
e
lan
g
u
ag
e
m
o
d
el
to
o
l
(
C
h
atGPT
3
.
5
)
.
Fiv
e
wid
ely
u
s
ed
au
to
m
ated
C
E
FR
tex
t
an
aly
ze
r
s
ch
o
s
en
f
o
r
th
is
s
tu
d
y
wer
e
C
ath
o
v
en
AI
,
tex
t
an
aly
ze
r
(
R
T
G
),
GSE
(
Pear
s
o
n
)
,
T
ex
t
I
n
s
p
ec
to
r
an
d
Ox
f
o
r
d
T
e
x
t
C
h
ec
k
er
(
Ox
f
o
r
d
L
ea
r
n
e
r
Dictio
n
ar
y
)
.
T
h
ese
o
n
lin
e
to
o
ls
ar
e
ac
ce
s
s
ib
le
o
n
lin
e.
C
ath
o
v
en
AI
p
r
o
v
id
es
m
an
y
au
to
m
ated
te
x
t
an
al
y
s
is
f
ea
tu
r
es
s
u
ch
as
a
r
ea
d
ab
ilit
y
a
n
a
ly
ze
r
an
d
C
E
FR
an
aly
ze
r
.
I
n
th
e
C
E
FR
an
aly
ze
r
,
a
u
s
er
ca
n
g
en
er
at
e
tex
t
o
u
t
p
u
t
r
esu
lts
with
a
g
en
er
al
C
E
FR
lev
el
b
r
ea
k
d
o
wn
f
r
o
m
v
o
ca
b
u
lar
y
,
v
er
b
f
o
r
m
,
a
n
d
clau
s
e.
Mo
r
eo
v
er
,
t
h
e
to
o
l
c
o
u
ld
also
p
r
o
v
id
e
lev
el
m
ap
p
in
g
o
f
p
r
o
v
id
e
d
tex
t
to
th
e
Am
er
ica
n
C
o
u
n
cil
o
n
th
e
T
ea
c
h
in
g
o
f
Fo
r
eig
n
L
an
g
u
ag
es
(
AC
T
FL)
,
B
r
itis
h
C
o
u
n
cil,
I
E
L
T
S,
an
d
C
am
b
r
id
g
e
Scale.
T
h
e
v
o
ca
b
u
lar
y
b
r
ea
k
d
o
w
n
in
clu
d
es
v
o
ca
b
u
lar
y
k
n
o
wl
ed
g
e
d
e
m
an
d
s
.
T
h
e
Ox
f
o
r
d
5
0
0
0
wo
r
d
lis
t
was
u
s
ed
in
th
is
s
tu
d
y
as
it
is
an
e
x
p
an
d
e
d
c
o
r
e
wo
r
d
lis
t
f
o
r
ad
v
an
ce
d
lear
n
er
s
o
f
E
n
g
lis
h
,
in
clu
d
i
n
g
th
e
2
0
0
0
w
o
r
d
s
f
o
r
lear
n
er
s
at
B
2
-
C
1
.
Ov
er
all,
ten
te
x
ts
o
f
B
1
an
d
te
n
tex
ts
o
f
B
2
wer
e
co
m
p
u
ted
f
o
r
C
E
FR
lev
el.
T
h
is
ac
c
o
u
n
ts
f
o
r
a
s
u
m
o
f
twen
ty
tex
ts
to
b
e
a
u
to
m
ati
ca
lly
an
aly
ze
d
.
As
m
o
s
t
C
E
FR
an
aly
ze
r
to
o
ls
p
r
o
v
id
e
o
n
ly
q
u
an
titativ
e
r
esu
lts
b
ased
o
n
d
if
f
er
en
t
m
etr
ics,
th
e
d
escr
ip
tiv
e
ac
co
u
n
t
o
f
a
tex
t
is
o
f
ten
lim
ited
.
T
h
is
is
b
ec
au
s
e
class
if
icatio
n
ap
p
r
o
ac
h
es
o
f
C
E
FR
tex
ts
co
u
ld
b
e
f
r
o
m
a
co
r
p
u
s
-
b
ase
d
ap
p
r
o
ac
h
o
r
a
co
m
p
lex
m
ath
em
atica
l
m
o
d
el
r
ea
d
ab
ilit
y
ass
ess
m
en
t
[
2
2
]
.
H
en
ce
,
C
h
atGPT
3
.
5
as
o
n
e
o
f
t
h
e
ad
v
an
ce
d
lan
g
u
ag
e
m
o
d
els
was
ad
d
ed
s
in
ce
it
h
as
b
ee
n
tr
ain
ed
o
n
a
v
ast
c
o
r
p
u
s
o
f
te
x
ts
an
d
co
u
ld
p
r
o
v
id
e
co
m
p
lex
m
ath
em
atica
l
m
o
d
els
s
u
ch
as
Fles
ch
Kin
ca
id
s
co
r
e
t
o
ar
r
iv
e
at
a
p
a
r
ticu
lar
C
E
FR
lev
el.
T
h
er
e
f
o
r
e,
it
was
in
clu
d
e
d
as o
n
e
o
f
th
e
au
to
m
ated
to
o
ls
t
o
an
aly
ze
tex
t
an
d
class
if
y
tex
ts
in
to
C
E
F
R
lev
el.
T
h
e
p
r
o
m
p
t
g
iv
en
to
th
e
C
h
atGPT
3
.
5
was
“a
n
aly
ze
a
tex
t
g
iv
en
an
d
class
if
y
it in
to
C
E
FR
lev
el
.
”
3
.
3
.
Da
t
a
a
na
ly
s
is
T
h
e
an
aly
s
is
in
v
o
lv
es
an
e
v
alu
atio
n
o
f
t
h
e
co
n
s
is
ten
cy
an
d
ac
cu
r
ac
y
o
f
th
e
C
E
FR
tex
t
class
if
icatio
n
to
o
ls
b
y
u
s
in
g
d
escr
ip
tiv
e
s
tatis
tical
m
ea
s
u
r
es
f
o
r
ea
ch
to
o
l.
Fo
r
ea
ch
o
f
th
e
20
tex
t
s
am
p
le
s
,
th
e
C
E
FR
lev
els
ass
ig
n
ed
b
y
th
e
s
ix
web
-
b
ase
d
to
o
ls
(
C
h
atGPT
3
.
5
,
C
ath
o
v
en
AI
,
R
T
G
T
ex
t
An
al
y
ze
r
,
G
SE,
T
ex
t
I
n
s
p
ec
to
r
,
an
d
Ox
f
o
r
d
T
ex
t
C
h
ec
k
er
)
a
r
e
r
ec
o
r
d
ed
.
T
en
t
ex
ts
u
s
ed
f
o
r
d
escr
ip
tiv
e
s
tatis
tical
an
aly
s
is
ar
e
b
ased
o
n
th
e
av
ailab
ilit
y
o
f
tex
t
f
r
o
m
th
e
s
am
e
s
o
u
r
ce
o
f
L
in
g
u
a.
co
m
.
T
o
f
ac
ilit
ate
n
u
m
er
ical
an
aly
s
is
,
C
E
FR
lev
els
ar
e
ass
ig
n
ed
n
u
m
er
ical
v
alu
es:
A
1
as
1
,
A2
as
2
,
B
1
as
3
,
B
2
as
4
,
C
1
as
5
,
an
d
C
2
as
6
.
Usi
n
g
d
escr
ip
tiv
e
s
tatis
t
ics
is
es
s
en
tial
in
th
is
p
r
o
ce
s
s
as
th
e
m
ea
n
,
m
e
d
ian
,
m
o
d
e,
a
n
d
s
tan
d
a
r
d
d
e
v
iatio
n
(
SD)
o
f
th
e
ass
ig
n
ed
C
E
FR
lev
els
ar
e
ca
lcu
lated
f
o
r
ea
ch
to
o
l
to
s
u
m
m
ar
ize
d
atasets
in
to
b
asic
m
ea
s
u
r
es,
m
ak
in
g
it
ea
s
ier
to
co
m
p
ar
e
a
n
d
in
ter
p
r
et
t
h
e
p
e
r
f
o
r
m
an
ce
o
f
ea
ch
to
o
l.
T
h
e
m
e
an
p
r
o
v
id
es a
n
av
er
ag
e
p
r
o
f
ici
en
cy
lev
el
ass
ig
n
ed
b
y
ea
ch
to
o
l w
h
ich
co
u
ld
o
f
f
er
a
b
en
ch
m
ar
k
f
o
r
co
m
p
ar
is
o
n
.
T
h
e
m
ed
ian
in
d
icate
s
th
e
ce
n
t
r
al
ten
d
en
cy
o
f
th
e
ass
ig
n
ed
lev
els,
an
d
th
e
m
o
d
e
ca
n
g
iv
e
th
e
m
o
s
t f
r
eq
u
en
tly
a
s
s
i
g
n
ed
lev
els,
wh
ich
ca
n
s
h
o
w
wh
er
e
to
o
ls
m
o
s
t
co
m
m
o
n
l
y
ag
r
ee
.
SD
m
ea
s
u
r
es
th
e
v
ar
iatio
n
o
r
d
is
p
er
s
io
n
o
f
th
e
ass
ig
n
ed
C
E
FR
lev
els,
in
d
icatin
g
th
e
co
n
s
is
ten
cy
o
f
ea
ch
to
o
l'
s
class
if
icatio
n
s
.
I
t
m
u
s
t
b
e
n
o
ted
,
h
o
wev
e
r
,
th
at
th
e
s
tu
d
y
d
o
es
n
o
t
i
n
ten
d
to
a
p
p
ly
p
u
r
ely
d
escr
ip
tiv
e
s
tatis
tics
a
s
a
m
ajo
r
an
aly
s
is
m
eth
o
d
s
in
ce
:
i)
th
e
n
u
m
b
er
o
f
tex
ts
is
lim
it
ed
to
o
n
ly
10
tex
ts
an
d
ii)
ea
ch
au
to
m
ated
to
o
l
u
s
es
a
d
if
f
er
en
t
alg
o
r
ith
m
an
d
f
r
am
ewo
r
k
to
an
aly
ze
th
e
tex
ts
au
to
m
atica
lly
.
As
a
r
esu
lt,
th
e
g
en
er
ate
d
C
E
FR
le
v
el
an
d
tex
t c
o
n
ten
t a
r
e
u
s
ed
t
o
q
u
alitativ
ely
an
al
y
ze
th
e
r
es
u
lt.
4.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
ab
le
3
an
d
Fig
u
r
e
1
p
r
esen
t
t
h
e
C
E
FR
lev
els
ass
ig
n
ed
b
y
e
ac
h
to
o
l
f
o
r
th
e
te
n
B
1
tex
ts
.
T
h
e
m
ea
n
C
E
FR
lev
el
a
s
s
ig
n
ed
b
y
C
h
atGPT
3
.
5
was
3
.
2
0
,
in
d
icatin
g
a
B
1
lev
el,
with
a
m
ed
ian
o
f
3
.
0
0
a
n
d
a
m
o
d
e
o
f
3
.
0
0
,
s
h
o
win
g
a
c
o
n
s
is
ten
t
class
if
icatio
n
with
in
th
e
B
1
r
an
g
e.
T
h
e
SD
o
f
0
.
4
2
s
u
g
g
e
s
ts
th
at
it
h
as
lo
w
v
ar
iab
ilit
y
in
th
e
class
if
icatio
n
s
b
y
C
h
at
GPT3
.
5
.
C
ath
o
v
en
AI
v
er
s
io
n
2
.
0
ass
ig
n
ed
a
m
ea
n
C
E
FR
lev
el
o
f
3
.
5
(
B
1
+)
,
s
u
g
g
esti
n
g
th
at
m
o
s
t
t
ex
ts
wer
e
class
if
ied
with
in
th
e
u
p
p
er
-
i
n
ter
m
ed
iate
r
a
n
g
e
o
f
in
d
ep
e
n
d
en
t
u
s
er
s
.
T
h
e
m
e
d
ian
a
n
d
m
o
d
e
wer
e
b
o
th
r
ec
o
r
d
e
d
at
3
.
0
0
(
B
1
)
,
in
d
icatin
g
th
at
th
e
m
o
s
t
f
r
e
q
u
en
t
cla
s
s
if
icatio
n
r
em
ain
ed
at
th
e
lo
wer
en
d
o
f
th
e
B
1
lev
el.
T
h
e
SD
o
f
0
.
7
0
r
ev
ea
ls
a
h
ig
h
e
r
d
eg
r
ee
o
f
v
a
r
iatio
n
i
n
th
e
ass
ig
n
ed
lev
els,
s
u
g
g
esti
n
g
less
co
n
s
is
ten
cy
in
co
m
p
ar
is
o
n
to
o
th
e
r
an
aly
ze
r
s
.
T
h
is
v
ar
iab
ilit
y
im
p
lies
th
at
C
ath
o
v
en
AI
m
ay
class
if
y
tex
ts
with
m
o
r
e
f
lu
ctu
atio
n
,
p
o
ten
tially
in
f
l
u
en
cin
g
its
r
eliab
ilit
y
f
o
r
p
r
ec
is
e
C
E
FR
al
ig
n
m
en
t.
T
h
e
GSE
T
ex
t
A
n
aly
ze
r
(
Pear
s
o
n
)
co
n
s
is
ten
tly
ass
ig
n
ed
a
m
ea
n
C
E
FR
lev
el
o
f
4
.
0
5
(
B
2
)
,
in
d
icatin
g
th
at
m
o
s
t
tex
ts
wer
e
clas
s
if
ie
d
at
th
e
u
p
p
er
-
in
ter
m
ed
iate
le
v
el.
B
o
th
th
e
m
ed
ian
an
d
m
o
d
e
wer
e
r
ec
o
r
d
e
d
at
4
.
0
0
(
B
2
)
,
co
n
f
ir
m
in
g
th
at
th
e
m
ajo
r
ity
o
f
class
if
icatio
n
s
r
em
ain
ed
s
tab
le
at
th
is
p
r
o
f
icien
cy
lev
el.
T
h
e
SD
o
f
0
.
1
5
s
u
g
g
ests
m
in
im
al
v
a
r
ia
tio
n
,
d
em
o
n
s
tr
atin
g
t
h
at
th
e
to
o
l
p
r
o
d
u
ce
d
h
ig
h
ly
co
n
s
i
s
ten
t
r
esu
lts
ac
r
o
s
s
d
if
f
er
en
t
tex
ts
.
T
h
is
co
n
s
is
te
n
cy
in
d
icate
s
th
at
th
e
GSE
T
ex
t
An
a
ly
ze
r
p
r
o
v
i
d
es
a
r
eliab
le
b
en
ch
m
ar
k
f
o
r
B2
-
lev
el
tex
t c
lass
if
icatio
n
wit
h
litt
le
f
lu
ctu
atio
n
in
its
ass
ess
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en
ts
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2252
-
8
8
2
2
I
n
t
J
E
v
al
&
R
es E
d
u
c
,
Vo
l
.
14
,
No
.
4
,
Au
g
u
s
t
20
25
:
3
2
8
3
-
3
2
9
4
3288
T
ex
t
I
n
s
p
ec
to
r
ass
ig
n
ed
a
m
ea
n
C
E
FR
lev
el
o
f
5
.
5
0
(
C
1
+)
,
i
n
d
icatin
g
t
h
at
m
o
s
t
a
n
aly
ze
d
t
ex
ts
wer
e
class
if
ied
with
in
th
e
ad
v
an
ce
d
p
r
o
f
icien
cy
r
a
n
g
e.
B
o
th
th
e
m
ed
ian
an
d
m
o
d
e
we
r
e
also
r
ec
o
r
d
ed
at
5
.
5
0
(
C
1
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,
s
h
o
win
g
th
at
th
e
m
o
s
t
f
r
eq
u
e
n
t
an
d
ce
n
tr
al
class
if
ica
tio
n
s
r
em
ain
ed
at
th
e
s
am
e
le
v
el.
T
h
e
SD
o
f
0
.
3
7
s
u
g
g
ests
th
at
wh
ile
th
er
e
was
s
o
m
e
v
ar
iatio
n
in
th
e
ass
ig
n
ed
lev
els,
th
e
class
if
icatio
n
s
d
id
n
o
t
f
lu
ctu
ate
d
r
asti
ca
lly
.
Ov
er
all,
th
is
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esu
l
t
in
d
icate
s
th
at
th
e
T
ex
t
I
n
s
p
ec
to
r
co
n
s
is
ten
tly
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ated
th
e
tex
ts
at
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ad
v
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ce
d
lev
el
with
o
n
ly
m
i
n
o
r
d
ev
iatio
n
s
in
class
if
icatio
n
.
T
h
e
T
e
x
t
A
n
al
y
ze
r
(
R
T
G
)
ass
i
g
n
e
d
a
m
ea
n
C
E
FR
le
v
e
l o
f
4
.
7
0
(
B
2
+
)
,
s
u
g
g
esti
n
g
th
at
t
h
e
m
aj
o
r
it
y
o
f
tex
ts
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er
e
cl
ass
if
ie
d
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h
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n
t
h
e
u
p
p
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r
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i
n
te
r
m
e
d
ia
te
t
o
ad
v
an
ce
d
r
a
n
g
e
.
T
h
e
m
ed
ia
n
an
d
m
o
d
e
w
e
r
e
b
o
t
h
r
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co
r
d
e
d
at
5
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0
0
(
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1
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,
i
n
d
ic
ati
n
g
th
at
t
h
e
m
o
s
t
co
m
m
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n
c
las
s
if
i
ca
t
io
n
p
la
ce
d
te
x
ts
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t
t
h
e
p
r
o
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cie
n
t
l
e
v
el
.
T
h
e
SD
o
f
0
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4
8
r
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lec
ts
m
o
d
e
r
at
e
v
a
r
i
ab
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y
,
m
ea
n
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n
g
t
h
at
w
h
il
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s
o
m
e
t
e
x
ts
we
r
e
r
ate
d
l
o
w
er
o
r
h
i
g
h
e
r
,
t
h
e
t
o
o
l
m
ai
n
t
ai
n
e
d
a
r
el
ati
v
e
ly
s
t
a
b
le
class
i
f
i
ca
t
io
n
t
r
e
n
d
.
T
h
is
p
att
e
r
n
s
u
g
g
ests
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h
a
t
R
T
G
te
n
d
s
t
o
ass
ig
n
C
E
FR
l
ev
els
in
a
r
an
g
e
b
e
twe
en
B
2
+
a
n
d
C
1
,
d
e
m
o
n
s
t
r
ati
n
g
a
d
e
g
r
e
e
o
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c
o
n
s
is
te
n
cy
b
u
t w
it
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o
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le
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l
u
ct
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ati
o
n
s
.
T
h
e
Ox
f
o
r
d
T
ex
t
C
h
ec
k
er
p
r
o
v
id
ed
o
n
ly
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r
d
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er
ce
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e
d
ata
r
ath
er
th
an
ass
ig
n
in
g
a
n
o
v
er
all
C
E
FR
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el
to
th
e
tex
ts
.
T
h
e
r
esu
lts
in
d
icate
d
th
at
th
e
m
ajo
r
ity
o
f
wo
r
d
s
in
th
e
an
al
y
ze
d
te
x
ts
wer
e
class
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ied
at
th
e
A1
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el,
r
ef
lectin
g
b
asic
v
o
ca
b
u
lar
y
u
s
ag
e.
Ad
d
itio
n
a
lly
,
wo
r
d
s
at
th
e
B
1
lev
el
ac
c
o
u
n
ted
f
o
r
o
n
ly
5
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to
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th
e
to
tal
wo
r
d
co
u
n
t,
s
u
g
g
esti
n
g
lim
ited
lex
ical
co
m
p
lex
ity
.
T
h
is
d
ata
im
p
lies
th
at
th
e
Ox
f
o
r
d
T
e
x
t
C
h
ec
k
er
ten
d
s
to
class
if
y
tex
t
s
at
a
lo
w
er
p
r
o
f
icien
c
y
lev
el
b
ased
p
r
im
ar
ily
o
n
wo
r
d
f
r
e
q
u
en
cy
r
ath
er
th
a
n
b
r
o
ad
e
r
lin
g
u
is
tic
f
ea
tu
r
es.
T
ab
le
3
.
Au
to
m
ated
C
E
FR
an
aly
ze
r
f
o
r
B
1
tex
ts
Ti
t
l
e
o
f
te
xt
To
t
a
l
w
o
r
d
c
o
u
n
t
C
h
a
t
G
P
T
3
.
5
C
a
t
h
o
v
e
n
A
I
V
e
r
si
o
n
2
.
0
(
g
e
n
e
r
a
l
l
e
v
e
l
)
G
S
E
Te
x
t
A
n
a
l
y
z
e
r
(
P
e
a
r
so
n
)
Te
x
t
I
n
sp
e
c
t
o
r
(
o
v
e
r
a
l
l
l
e
x
i
c
a
l
p
r
o
f
i
l
e
)
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x
t
A
n
a
l
y
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r
(
R
TG
)
O
x
f
o
r
d
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x
t
C
h
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k
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r
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O
x
f
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d
Le
a
r
n
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r
D
i
c
t
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o
n
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r
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)
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o
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d
l
i
s
t
O
x
f
o
r
d
5
0
0
0
Th
e
Em
p
i
r
e
S
t
a
t
e
B
u
i
l
d
i
n
g
2
4
7
3
(
B
1
)
3
(
B
1
)
4
(
B
2
)
5
.
5
(
C
1
+
)
5
(
C
1
)
A
1
(
7
1
%)
(
W
i
t
h
B
1
a
t
5
%)
S
a
n
F
r
a
n
c
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sc
o
2
6
0
4
(
B
2
)
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(
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1
)
4
(
B
2
)
5
(
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1
)
4
(
B
2
)
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1
(
7
1
%)
(
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i
t
h
B
1
a
t
4
%)
C
h
i
c
a
g
o
2
3
6
4
(
B
2
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3
(
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1
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(
B
2
)
5
(
C
1
+
)
5
(
C
1
)
A
1
(
6
6
%)
(
W
i
t
h
B
1
a
t
6
%)
Th
e
S
t
a
t
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e
o
f
Li
b
e
r
t
y
2
4
8
3
(
B
1
)
4
(
B
2
)
4
(
B
2
)
6
(
C
2
)
5
(
C
1
)
A
1
(
6
9
%)
(
W
i
t
h
B
1
a
t
8
%)
Th
e
G
r
a
n
d
C
a
n
y
o
n
2
5
2
3
(
B
1
)
4
(
B
2
)
4
(
B
2
)
5
.
5
(
C
1
+
)
4
(
B
2
)
A
1
(
6
9
%)
(
W
i
t
h
B
1
a
t
8
%)
Lo
s A
n
g
e
l
e
s
2
1
9
3
(
B
1
)
4
(
B
1
)
4
.
5
(
B
2
+
)
5
.
5
(
C
1
+
)
5
(
C
1
)
A
1
(
6
1
%)
(
W
i
t
h
B
1
a
t
6
%)
M
i
a
mi
2
5
3
3
(
B
1
)
3
(
B
1
)
4
(
B
2
)
5
.
5
(
C
1
+
)
5
(
C
1
)
A
1
(
7
0
%)
(
W
i
t
h
B
1
a
t
2
%)
W
a
sh
i
n
g
t
o
n
,
D
.
C
.
1
9
2
3
(
B
1
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3
(
B
1
)
4
(
B
2
)
5
.
5
(
C
1
+
)
4
(
B
2
)
A
1
(
6
5
%)
(
W
i
t
h
B
1
a
t
2
%)
Y
e
l
l
o
w
st
o
n
e
N
a
t
i
o
n
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l
P
a
r
k
2
6
8
3
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B
1
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3
(
B
1
)
4
(
B
2
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6
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C
2
)
5
(
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1
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1
(
6
9
%)
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W
i
t
h
B
1
a
t
4
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V
a
l
e
n
t
i
n
e
’
s Da
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1
7
1
3
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B
2
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5
(
C
1
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4
(
B
2
)
6
(
C
2
)
5
(
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1
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A
1
(
6
3
%)
(
W
i
t
h
B
1
a
t
4
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M
e
a
n
(
C
EF
R
l
e
v
e
l
)
-
3
.
2
0
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1
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3
.
5
(
B
1
+
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4
.
0
5
(
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2
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5
.
5
0
(
C
1
+
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4
.
7
0
(
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2
+
)
-
M
e
d
i
a
n
(
C
EF
R
l
e
v
e
l
)
-
3
.
0
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1
)
3
.
0
0
(
B
1
)
4
.
0
0
(
B
2
)
5
.
5
0
(
C
1
+
)
5
.
0
0
(
C
1
)
-
M
o
d
e
(
C
EF
R
l
e
v
e
l
)
-
3
.
0
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1
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3
.
0
0
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1
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4
.
0
0
(
B
2
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5
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5
0
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C
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+
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5
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0
0
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1
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-
SD
-
0
.
4
2
0
.
7
0
0
.
1
5
0
.
3
7
0
.
4
8
-
Fig
u
r
e
1
.
Au
t
o
m
ated
C
E
FR
an
aly
ze
r
m
ap
p
i
n
g
f
o
r
B
1
te
x
ts
T
EX
T
1
T
EX
T
2
T
EX
T
3
T
EX
T
4
T
EX
T
5
T
EX
T
6
T
EX
T
7
T
EX
T
8
T
EX
T
9
T
EX
T
1
0
A
1
A
2
B1
B2
C1
C2
Ch
a
tG
P
T
3
.
5
Ca
th
o
v
e
n
A
I
RT
G
T
e
x
t
A
n
a
ly
se
r
G
S
E
T
e
x
t
In
sp
e
c
to
r
Ox
f
o
rd
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J
E
v
al
&
R
es E
d
u
c
I
SS
N:
2252
-
8
8
2
2
E
va
lu
a
tin
g
t
h
e
co
n
s
is
ten
cy
o
f
a
u
to
ma
ted
C
E
F
R
a
n
a
lyzer
s
:
a
s
tu
d
y
o
f E
n
g
lis
h
…
(
P
iya
th
a
t
S
ir
ip
o
l
)
3289
T
ab
le
4
an
d
Fig
u
r
e
2
s
h
o
w
th
e
C
E
F
R
lev
els
ass
ig
n
ed
b
y
ea
c
h
to
o
l
f
o
r
th
e
ten
B
2
tex
ts
.
C
h
atGPT
3
.
5
h
ad
a
m
ea
n
C
E
FR
lev
el
o
f
3
.
5
0
(
B
1
/B
2
)
,
with
a
m
e
d
ian
o
f
3
.
5
0
(
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1
/B
2
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a
n
d
a
m
o
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e
o
f
3
.
0
0
(
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1
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.
T
h
e
SD
was 0
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5
3
,
in
d
icatin
g
m
o
d
er
ate
v
ar
iab
ilit
y
.
C
ath
o
v
en
AI
V
er
s
io
n
2
.
0
ass
ig
n
ed
a
m
ea
n
C
E
FR
lev
el
o
f
3
.
4
0
(
B
1
)
,
i
n
d
icatin
g
th
at
m
o
s
t
tex
ts
wer
e
class
if
ied
with
in
th
e
lo
wer
-
in
ter
m
ed
iate
r
an
g
e.
T
h
e
m
ed
i
an
an
d
m
o
d
e
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e
b
o
th
r
ec
o
r
d
ed
at
3
.
0
0
(
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1
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,
s
u
g
g
esti
n
g
th
at
th
e
m
ajo
r
ity
o
f
class
if
icatio
n
s
clu
s
ter
ed
ar
o
u
n
d
th
e
B
1
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el.
T
h
e
SD
o
f
0
.
5
2
r
ef
lects m
o
d
er
at
e
v
ar
iab
ilit
y
,
m
ea
n
in
g
th
at
s
o
m
e
tex
ts
wer
e
r
ated
s
lig
h
tly
ab
o
v
e
o
r
b
el
o
w
th
is
lev
el.
T
h
is
d
eg
r
ee
o
f
f
lu
ctu
atio
n
s
u
g
g
ests
th
at
wh
ile
C
ath
o
v
e
n
AI
g
en
e
r
ally
alig
n
s
with
th
e
B
1
class
if
icatio
n
,
its
ass
es
s
m
en
ts
m
ay
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2252
-
8
8
2
2
I
n
t
J
E
v
al
&
R
es E
d
u
c
,
Vo
l
.
14
,
No
.
4
,
Au
g
u
s
t
20
25
:
3
2
8
3
-
3
2
9
4
3290
Fig
u
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Au
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ated
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An
aly
ze
r
an
d
T
ex
t
I
n
s
p
ec
to
r
.
T
h
is
v
ar
iab
ilit
y
ca
n
b
e
attr
ib
u
ted
to
th
e
d
is
tin
ct
alg
o
r
ith
m
s
an
d
lin
g
u
is
tic
f
ea
tu
r
es
ea
ch
to
o
l
em
p
h
asizes.
C
h
atGPT
,
f
o
r
ex
am
p
le,
u
tili
ze
s
ad
v
an
ce
d
NL
P
tech
n
iq
u
es,
wh
er
ea
s
GSE
an
d
T
ex
t
I
n
s
p
ec
to
r
r
ely
o
n
m
o
r
e
tr
ad
itio
n
al
r
ea
d
a
b
ilit
y
m
etr
ics
an
d
lex
ical
p
r
o
f
ilin
g
f
r
a
m
ewo
r
k
s
.
T
h
e
m
ea
n
C
E
FR
lev
els
ass
ig
n
ed
b
y
th
e
to
o
ls
s
h
o
w
a
r
a
n
g
e
f
r
o
m
B
1
to
C
1
+
f
o
r
B
1
tex
ts
an
d
f
r
o
m
B
1
to
C
2
f
o
r
B
2
tex
ts
.
Su
ch
b
r
o
ad
r
an
g
es
in
d
icate
a
lack
o
f
co
n
s
en
s
u
s
am
o
n
g
t
h
e
to
o
ls
,
wh
ich
co
u
ld
lead
to
ch
allen
g
es
in
s
tan
d
ar
d
izin
g
tex
t
d
if
f
icu
lty
lev
els
ac
r
o
s
s
d
if
f
er
en
t e
d
u
ca
tio
n
al
co
n
te
x
ts
f
o
r
teac
h
er
s
,
m
ater
ial
d
ev
el
o
p
er
s
,
an
d
ev
en
p
o
licy
m
ak
er
s
.
A
lig
n
m
en
t v
alid
ity
is
a
co
n
ce
r
n
f
o
r
C
E
FR
[
2
3
]
an
d
ca
n
b
e
a
ch
allen
g
e
in
p
r
o
v
id
in
g
c
o
h
er
e
n
t
r
esu
lts
.
Fo
r
in
s
tan
ce
,
it
is
s
till
q
u
esti
o
n
ab
le
wh
et
h
er
d
if
f
er
e
n
t
r
ea
d
er
s
at
th
e
s
am
e
B
2
lev
el
c
an
p
er
f
o
r
m
all
th
e
task
s
d
escr
ib
ed
in
A1
a
n
d
A2
.
An
o
n
g
o
in
g
d
is
cu
s
s
io
n
o
f
wh
eth
er
to
tak
e
lin
g
u
is
tic
q
u
ality
an
d
q
u
an
tity
as
a
m
ea
s
u
r
e
o
f
lan
g
u
ag
e
a
b
ilit
y
is
s
till
in
q
u
esti
o
n
.
T
h
er
e
is
n
o
e
m
p
ir
ical
ev
id
en
ce
to
s
u
p
p
o
r
t
t
h
at
lan
g
u
ag
e
lear
n
er
s
at
a
B
2
lev
el
ca
n
d
o
all
th
e
A2
task
s
to
r
ea
ch
B
2
.
He
n
ce
,
m
o
r
e
r
esear
ch
is
n
ee
d
ed
to
ex
p
lo
r
e
d
if
f
er
en
t
d
im
en
s
io
n
s
o
f
C
E
FR
th
at
a
r
e
s
till
u
n
k
n
o
wn
.
Fo
r
in
s
tan
ce
,
it c
o
u
l
d
b
e
s
ee
n
f
r
o
m
th
e
f
in
d
in
g
s
th
at
th
e
to
p
ic
o
r
co
n
ten
t o
f
a
p
ass
ag
e
m
ay
in
f
lu
en
ce
th
e
o
v
er
all
o
u
tco
m
e
o
f
C
E
FR
lev
el
b
y
au
t
o
m
ated
in
s
tr
u
m
e
n
t
s
.
I
t
is
n
o
tewo
r
th
y
to
m
en
tio
n
th
at
ac
r
o
s
s
th
ese
ten
B
1
tex
ts
,
9
o
u
t
o
f
1
0
s
to
r
ies
ar
e
ab
o
u
t
‘
lo
ca
tio
n
’
,
with
o
n
e
a
b
o
u
t
a
n
ev
e
n
t
(
Val
en
tin
e’
s
Day
)
.
E
x
am
in
in
g
th
e
au
to
m
ated
in
s
tr
u
m
en
ts
u
s
ed
,
i
t
ap
p
ea
r
s
th
at
m
o
s
t
au
to
m
ated
in
s
tr
u
m
e
n
ts
m
ap
o
n
e
lev
el
m
o
r
e
ad
v
a
n
ce
d
f
o
r
th
e
C
E
FR
.
Fo
r
in
s
tan
ce
,
C
h
at
G
PT
3
.
5
,
an
NL
P
to
o
l
with
a
m
ac
h
in
e
lear
n
in
g
alg
o
r
ith
m
,
g
e
n
er
ated
a
tex
t
ab
o
u
t
Vale
n
tin
e’
s
Day
to
b
e
at
th
e
l
ev
el
o
f
B
2
wh
e
r
ea
s
th
e
m
ajo
r
ity
o
f
o
th
er
to
o
ls
m
a
p
th
e
p
ass
ag
e
to
b
e
at
a
B
1
lev
el.
Similar
ly
,
th
e
r
esu
lt
f
r
o
m
th
e
B
2
tex
ts
s
h
o
ws
th
at
wh
en
a
p
ass
ag
e
is
ab
o
u
t
a
‘
lo
ca
tio
n
’
,
C
h
at
GPT
3
.
5
t
en
d
s
to
m
ap
th
em
to
b
e
at
t
h
e
B
1
lev
el,
with
h
is
to
r
ical
tex
t
p
ass
ag
es
(
B
en
jam
in
Fra
n
k
lin
an
d
t
h
e
Kite
a
n
d
Ho
t
Air
B
allo
o
n
s
:
A
Fu
n
His
to
r
y
)
an
d
with
h
is
to
r
ical
ev
en
ts
(
T
h
e
lo
n
g
es
t
an
d
m
o
s
t
s
ce
n
ic
T
r
ain
R
id
e)
to
b
e
at
th
e
B
2
lev
el.
C
o
m
p
ar
in
g
th
e
r
esu
lt
b
etwe
en
C
h
atGPT
3
.
5
an
d
t
h
e
lex
ical
p
r
o
f
ile
f
r
a
m
ewo
r
k
b
y
T
ex
t
I
n
s
p
ec
to
r
f
r
o
m
th
e
B
1
p
ass
ag
es,
T
e
x
t
I
n
s
p
ec
to
r
m
a
p
s
an
o
v
er
all
C
E
FR
o
f
a
s
to
r
y
ab
o
u
t
v
alen
ti
n
e’
s
d
ay
to
b
e
at
C
2
lev
el
wh
er
e
th
e
m
ajo
r
ity
p
ass
ag
es
r
elatin
g
to
‘
lo
ca
tio
n
’
ar
e
at
th
e
C
1
an
d
C
1
+
le
v
el.
Similar
to
th
e
p
ass
ag
es
f
r
o
m
B
2
tex
ts
,
th
e
lex
ical
p
r
o
f
ile
f
r
a
m
ewo
r
k
b
y
T
e
x
t
I
n
s
p
ec
to
r
m
ap
s
th
e
o
v
er
all
C
E
FR
lev
el
o
f
co
n
ten
t
ab
o
u
t
‘
lo
ca
ti
o
n
’
to
b
e
at
B
1
+
to
C
1
.
Ho
wev
er
,
wh
en
th
e
p
ass
ag
es
ar
e
a
b
o
u
t
‘
a
n
im
al’
o
r
‘
h
is
to
r
y
’
,
th
e
r
esu
lt
ch
a
n
g
es
t
o
C
2
(
An
im
al
a
n
d
B
en
jam
in
Fra
n
k
lin
an
d
th
e
Kite)
.
Her
e,
it
is
p
o
s
s
ib
le
th
at
co
n
ten
t
an
d
wo
r
d
s
u
s
ed
with
in
d
if
f
er
en
t
tex
t
g
en
r
es
m
ay
in
f
lu
e
n
ce
th
e
o
v
er
all
C
E
FR
lev
el,
s
im
ilar
to
th
e
co
n
tex
t
o
f
p
r
e
v
io
u
s
s
tu
d
ies
[2
4
]
,
[
2
5
]
.
No
t
o
n
ly
d
o
es
th
e
tr
ad
itio
n
al
lex
ical
p
r
o
f
ile
f
r
am
ew
o
r
k
f
r
o
m
T
ex
t
I
n
s
p
ec
to
r
s
h
o
w
an
i
n
ter
esti
n
g
r
esu
lt th
at
m
ay
b
e
in
f
lu
en
ce
d
b
y
wh
at
th
e
s
to
r
y
is
ab
o
u
t in
g
en
er
atin
g
th
e
o
v
e
r
all
C
E
FR
b
u
t a
ls
o
th
e
C
a
th
o
v
en
AI
v
er
s
io
n
2
.
0
.
Fro
m
B
1
tex
ts
,
C
ath
o
v
en
AI
g
en
er
ated
9
o
u
t
o
f
1
0
tex
ts
ab
o
u
t
a
lo
ca
tio
n
t
o
b
e
at
B
1
-
B
2
lev
el
with
o
n
ly
o
n
e
to
th
e
C
1
lev
el.
Similar
to
th
e
p
r
ev
io
u
s
au
to
m
ated
in
s
tr
u
m
en
ts
,
C
ath
o
v
e
n
AI
g
en
er
ated
an
o
v
er
all
C
E
FR
lev
el
f
o
r
v
alen
tin
e’
s
d
ay
to
b
e
C
1
.
Similar
t
o
th
e
g
r
o
u
p
o
f
B
1
tex
ts
,
C
ath
o
v
en
AI
ap
p
ea
r
s
to
T
E
XT
1
T
E
XT
2
T
E
XT
3
T
E
XT
4
T
E
XT
5
T
E
X
T
6
T
E
XT
7
T
E
XT
8
T
E
XT
9
T
E
XT
10
A
1
A
2
B1
B2
C1
C2
Ch
a
tGP
T
3
.
5
C
ath
o
v
en
A
I
R
T
G
T
ex
t A
n
aly
s
er
GSE
T
ex
t I
n
s
p
ec
to
r
Ox
f
o
r
d
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J
E
v
al
&
R
es E
d
u
c
I
SS
N:
2252
-
8
8
2
2
E
va
lu
a
tin
g
t
h
e
co
n
s
is
ten
cy
o
f
a
u
to
ma
ted
C
E
F
R
a
n
a
lyzer
s
:
a
s
tu
d
y
o
f E
n
g
lis
h
…
(
P
iya
th
a
t
S
ir
ip
o
l
)
3291
r
ate
m
o
s
t
B
2
te
x
ts
as
B
1
with
o
n
ly
a
f
ew
at
B
2
,
esp
ec
ially
wh
en
th
e
to
p
ic
is
r
elate
d
t
o
h
i
s
to
r
ical
tex
t
ty
p
es.
T
h
is
s
h
o
ws
th
at
th
e
tex
t
ab
o
u
t
v
alen
tin
e’
s
d
ay
m
ay
co
n
tain
wo
r
d
s
,
p
h
r
ases
,
o
r
g
r
am
m
a
tical
s
tr
u
ctu
r
es
th
at
m
ay
b
e
m
o
r
e
c
o
m
p
lex
o
r
in
f
r
eq
u
en
t.
C
o
m
p
a
r
ed
to
all
au
t
o
m
ated
in
s
tr
u
m
en
ts
,
T
ex
t
I
n
s
p
ec
to
r
m
ap
s
a
tex
t
ab
o
u
t
v
alen
tin
e’
s
d
a
y
to
b
e
at
th
e
h
ig
h
est
lev
el
o
f
C
E
FR
at
C
2
.
T
o
ex
a
m
in
e
f
u
r
th
er
,
th
e
s
co
r
ec
ar
d
f
r
o
m
T
ex
t
I
n
s
p
ec
to
r
was
in
v
esti
g
ated
wh
ich
s
h
o
ws
th
at
th
e
o
v
e
r
all
C
E
FR
d
eter
m
in
ed
b
y
t
h
e
lex
ical
s
o
p
h
is
ticatio
n
f
r
o
m
th
e
E
VP
an
d
B
N
C
is
at
C
2
+.
T
h
is
in
d
icate
s
th
at
alth
o
u
g
h
a
co
r
p
u
s
-
b
ased
ap
p
r
o
ac
h
m
ay
p
r
o
v
i
d
e
u
s
er
s
with
f
ast
an
d
c
o
n
s
is
ten
t
r
esu
lts
in
g
en
er
atin
g
tex
t
d
if
f
icu
lty
b
as
ed
o
n
th
e
C
E
FR
g
u
id
elin
es,
t
h
e
ac
cu
r
ac
y
o
f
th
e
g
en
er
ated
C
E
FR
in
d
icato
r
f
o
r
a
p
ar
ticu
lar
tex
t
n
ee
d
s
to
b
e
ca
r
ef
u
lly
in
ter
p
r
eted
.
Pre
v
io
u
s
s
tu
d
ies
h
av
e
ex
p
lo
r
ed
d
if
f
e
r
en
t
asp
ec
ts
o
f
C
E
FR
lin
g
u
is
tic
f
ea
tu
r
es
u
s
in
g
a
co
r
p
u
s
-
b
ased
ap
p
r
o
ac
h
,
b
u
t
m
o
s
t
r
elate
s
to
id
en
tifia
b
le
f
ea
tu
r
es,
n
o
t c
o
n
c
ep
tu
al
ass
o
cia
tio
n
[
2
6
]
–
[
2
8
]
.
T
h
e
GSE
T
ex
t
An
aly
ze
r
b
y
P
ea
r
s
o
n
p
r
o
v
id
es
a
v
e
r
y
co
n
s
is
ten
t
r
esu
lt
(
S
D=
0
.
1
5
)
.
I
t
ca
n
b
e
s
ee
n
in
Fig
u
r
e
1
th
at
th
e
o
v
er
all
C
E
FR
r
esu
lt
g
en
er
ated
b
y
th
e
GSE
tex
t
an
aly
ze
r
is
v
er
y
co
n
s
is
ten
t
alth
o
u
g
h
th
e
in
ten
d
ed
lev
el
o
f
B
1
m
ay
n
o
t
m
atch
.
Sin
ce
th
e
GSE
tex
t
an
aly
ze
r
g
en
er
ated
th
e
v
alen
ti
n
e
’
s
d
ay
tex
t
to
b
e
at
B
2
,
an
o
th
er
tex
t
was
u
s
ed
to
co
m
p
ar
e
(
T
h
e
Gr
a
n
d
C
an
y
o
n
)
wh
ich
m
ap
p
ed
t
o
b
e
at
th
e
s
a
m
e
B
2
lev
el
b
y
th
e
GSE
T
ex
t
An
aly
ze
r
(
th
e
C
E
FR
lev
el
o
f
T
h
e
Gr
a
n
d
C
an
y
o
n
is
d
if
f
er
en
t
w
h
en
c
o
m
p
ar
e
d
b
y
o
th
er
tex
t
an
al
y
ze
r
p
r
o
g
r
a
m
s
)
.
Alig
n
m
en
t
o
f
s
co
r
es
o
f
th
e
GSE
s
ca
le
to
th
e
C
E
FR
is
s
h
o
wn
in
T
ab
le
5
.
T
h
e
GSE
s
ca
le
f
o
r
v
alen
tin
e’
s
d
ay
is
at
6
4
-
6
8
w
h
er
ea
s
T
h
e
Gr
an
d
C
an
y
o
n
is
at
6
2
-
6
6
.
T
h
e
GSE
r
a
n
g
e
f
o
r
B
1
2
is
at
5
9
-
7
5
,
th
er
ef
o
r
e,
t
h
e
r
esu
lt g
en
er
ate
d
b
y
th
e
GSE
tex
t a
n
aly
ze
r
is
n
o
t su
r
p
r
is
in
g
.
As in
ten
d
ed
b
y
th
e
Pear
s
o
n
r
esear
ch
team
,
GSE
co
u
ld
p
r
o
v
id
e
a
f
i
n
e
-
g
r
ain
g
r
an
u
lar
d
escr
ip
tiv
e
s
y
s
tem
to
d
ef
in
e
g
r
ad
ed
lear
n
in
g
,
teac
h
in
g
,
an
d
ass
es
s
m
en
t
o
b
jectiv
es.
T
h
is
im
p
lies
th
at
wh
ile
C
E
FR
ca
n
i
n
d
icate
th
e
d
if
f
icu
lty
lev
el
as
an
o
v
er
v
iew,
o
th
e
r
s
ca
les
co
u
ld
b
e
u
s
ed
as
an
ad
d
itio
n
al
m
ea
s
u
r
em
e
n
t
f
o
r
a
m
o
r
e
ac
cu
r
ate
r
e
p
r
esen
tatio
n
o
f
tex
t
d
if
f
icu
lty
.
Fig
u
r
e
2
s
h
o
ws
th
at
th
e
GSE
tex
t
an
aly
ze
r
ca
n
ac
c
u
r
ately
m
ap
th
e
lev
el
o
f
all
tex
ts
to
th
e
B
2
lev
el
as
th
e
tex
t
m
ater
ial
p
r
o
d
u
ce
r
s
in
ten
d
ed
t
o
p
r
o
d
u
ce
.
Mo
r
e
r
esear
ch
n
ee
d
s
to
b
e
d
o
n
e
o
n
th
e
lev
elin
g
o
f
tex
t
d
if
f
icu
lty
in
th
e
GSE
tex
t a
n
aly
ze
r
a
n
d
C
E
FR
,
esp
ec
ially
o
n
th
e
alig
n
m
e
n
t o
f
s
p
ec
if
ic
p
o
in
t r
a
n
g
es a
n
d
C
E
FR
lev
els
.
T
ab
le
5
.
Alig
n
m
e
n
t o
f
s
co
r
es to
th
e
C
E
FR
C
EFR
G
S
E
B
e
l
o
w
A
1
10
-
21
A1
22
-
29
A2
30
-
35
A
2
+
36
-
42
B1
43
-
50
B
1
+
51
-
58
B2
59
-
66
B
2
+
67
-
75
C1
76
-
84
C2
85
-
90
T
h
e
s
tu
d
y
f
in
d
i
n
g
s
co
u
ld
b
e
a
s
tar
tin
g
p
o
in
t
to
in
v
esti
g
ate
f
u
r
th
er
th
e
co
h
er
en
ce
o
f
au
to
m
ated
in
s
tr
u
m
en
ts
wh
en
an
aly
zin
g
C
E
FR
T
ex
t
s
.
User
s
m
ay
also
d
elv
e
in
to
lin
g
u
is
tic
f
ea
tu
r
es
o
f
tex
t,
n
o
t
o
n
ly
t
h
e
tr
ad
itio
n
al
lin
g
u
is
tic
f
ea
tu
r
es
l
ik
e
v
o
ca
b
u
lar
y
a
n
d
g
r
am
m
ar
p
o
in
ts
u
s
ed
b
u
t
also
co
n
s
id
er
t
h
e
r
o
le
o
f
co
n
ce
p
ts
em
b
ed
d
e
d
in
a
tex
t.
Fo
r
i
n
s
tan
ce
,
s
em
an
tic
ass
o
ciatio
n
as
o
n
e
o
f
th
e
lin
g
u
is
tic
f
ea
tu
r
es o
f
t
ex
t
m
ay
b
e
a
f
ac
t
o
r
in
in
f
lu
en
cin
g
tex
t
d
if
f
icu
lty
lev
el.
Alth
o
u
g
h
a
tex
t
id
en
tifie
d
to
b
e
at
th
e
s
am
e
lev
el
o
f
B
2
m
ay
b
e
ch
allen
g
in
g
to
r
ea
d
d
u
e
to
d
if
f
er
en
ce
s
in
c
o
n
ten
t
(
e.
g
.
,
h
is
to
r
y
,
n
ar
r
ativ
e,
an
d
s
cien
ce
f
ic
tio
n
)
,
th
e
p
atter
n
o
f
ab
s
tr
ac
t
co
n
ce
p
ts
e
m
b
ed
d
ed
in
th
e
c
o
n
ten
t
p
r
esen
ted
in
B
2
r
e
ad
in
g
m
ater
ials
is
o
f
ten
o
v
er
lo
o
k
ed
.
I
f
th
is
is
th
e
ca
s
e,
ad
d
itio
n
al
q
u
alitativ
e
m
etr
ics
m
ay
n
ee
d
to
b
e
p
r
o
p
o
s
ed
an
d
in
cl
u
d
ed
in
a
d
d
itio
n
to
th
e
tr
a
d
itio
n
al
q
u
an
titativ
e
m
ea
s
u
r
es a
n
d
AI
t
o
o
ls
av
ailab
le
to
d
ay
[
2
9
]
–
[
3
3
]
.
5.
CO
NCLU
SI
O
N
T
h
is
s
tu
d
y
h
ig
h
lig
h
ts
th
e
s
ig
n
if
ican
t
in
co
n
s
is
ten
cies
am
o
n
g
v
ar
io
u
s
au
t
o
m
ated
C
E
FR
tex
t
class
if
icatio
n
to
o
ls
,
in
clu
d
in
g
C
h
atGPT
3
.
5
,
C
ath
o
v
en
AI
,
GSE
T
ex
t
An
aly
ze
r
,
T
ex
t
I
n
s
p
ec
to
r
,
an
d
Ox
f
o
r
d
T
ex
t
C
h
ec
k
er
.
Desp
ite
ad
v
a
n
c
em
en
ts
in
NL
P
an
d
m
ac
h
in
e
l
ea
r
n
in
g
,
th
ese
to
o
ls
d
em
o
n
s
tr
a
te
v
ar
ied
r
esu
lts
f
o
r
th
e
s
am
e
tex
ts
,
u
n
d
er
s
co
r
in
g
th
e
co
m
p
lex
ity
a
n
d
c
h
allen
g
e
s
o
f
au
t
o
m
ated
tex
t
class
if
icatio
n
in
ed
u
ca
tio
n
al
s
ettin
g
s
.
T
r
ad
itio
n
al
r
ea
d
ab
ilit
y
m
etr
ics
an
d
lex
ical
p
r
o
f
ilin
g
f
r
am
ewo
r
k
s
o
f
ten
p
r
o
v
id
e
co
n
s
is
ten
t
b
u
t
h
i
g
h
er
-
lev
el
class
if
icatio
n
s
co
m
p
ar
ed
to
ad
v
an
ce
d
NL
P
-
b
ased
to
o
l
s
.
T
h
e
b
r
o
ad
r
an
g
e
o
f
C
E
FR
lev
els
ass
ig
n
ed
f
o
r
th
e
s
am
e
tex
ts
r
aise
s
co
n
ce
r
n
s
ab
o
u
t
r
eliab
ilit
y
an
d
s
tan
d
ar
d
izatio
n
,
wh
ich
ar
e
cr
itical
f
o
r
ed
u
ca
to
r
s
,
m
ater
ial
d
ev
elo
p
er
s
,
a
n
d
lan
g
u
ag
e
ass
ess
m
en
t
p
r
o
f
ess
io
n
als.
T
h
e
c
o
n
ten
t
an
d
g
en
r
e
o
f
te
x
ts
s
ig
n
if
ican
tly
in
f
lu
e
n
ce
C
E
FR
clas
s
if
icatio
n
,
in
d
icatin
g
a
n
ee
d
f
o
r
f
u
r
th
e
r
r
esear
ch
in
to
q
u
alitativ
e
asp
ec
ts
o
f
tex
t
class
if
icatio
n
,
in
clu
d
in
g
s
em
an
tic
ass
o
ciatio
n
s
an
d
th
em
atic
co
n
ten
t.
T
o
en
h
an
ce
th
e
r
eliab
ilit
y
an
d
ap
p
licab
ilit
y
o
f
th
ese
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2252
-
8
8
2
2
I
n
t
J
E
v
al
&
R
es E
d
u
c
,
Vo
l
.
14
,
No
.
4
,
Au
g
u
s
t
20
25
:
3
2
8
3
-
3
2
9
4
3292
to
o
ls
,
f
u
tu
r
e
r
esear
ch
s
h
o
u
ld
e
x
p
an
d
s
am
p
le
s
izes,
in
cl
u
d
e
d
i
v
er
s
e
tex
ts
,
an
d
i
n
teg
r
ate
q
u
ali
tativ
e
m
etr
ics
with
tr
ad
itio
n
al
q
u
an
titativ
e
m
ea
s
u
r
es.
C
o
n
tin
u
o
u
s
a
d
v
an
ce
m
en
t
s
an
d
v
alid
atio
n
ef
f
o
r
ts
ar
e
e
s
s
en
tial
to
im
p
r
o
v
e
th
e
ac
cu
r
ac
y
a
n
d
r
elia
b
ilit
y
o
f
au
to
m
ated
C
E
FR
tex
t
class
if
icatio
n
to
o
ls
f
o
r
e
f
f
ec
tiv
e
lan
g
u
ag
e
teac
h
i
n
g
an
d
ass
es
s
m
en
t.
As
co
m
m
u
n
icativ
e
lan
g
u
ag
e
teac
h
in
g
b
ec
o
m
es
m
o
r
e
p
r
o
m
i
n
en
t
ac
r
o
s
s
th
e
g
lo
b
e
,
th
e
C
E
FR
g
u
id
elin
e
p
r
o
v
i
d
es
wh
at
lan
g
u
ag
e
lear
n
e
r
s
n
ee
d
to
b
e
a
b
le
to
d
o
with
lan
g
u
a
g
e
at
d
if
f
er
en
t
lev
els,
n
o
t
h
o
w
m
an
y
co
m
p
lex
s
en
ten
ce
s
th
ey
ca
n
p
r
o
d
u
ce
.
T
h
er
ef
o
r
e,
th
e
u
s
e
o
f
l
an
g
u
a
g
e
d
if
f
e
r
s
s
in
ce
cu
ltu
r
al
b
ac
k
g
r
o
u
n
d
s
an
d
g
e
n
r
es a
r
e
alwa
y
s
in
v
o
lv
e
d
an
d
c
o
u
ld
b
e
r
ef
lecte
d
th
r
o
u
g
h
wr
itten
tex
t.
As
f
o
r
th
e
b
r
o
ad
er
co
m
m
u
n
it
y
,
o
n
e
s
ig
n
if
ica
n
t
f
in
d
in
g
th
a
t
th
e
s
tu
d
y
p
r
o
v
id
es
is
th
at
t
h
e
f
ield
o
f
co
m
p
u
ter
s
cien
ce
an
d
alg
o
r
ith
m
ic
d
ev
e
lo
p
er
s
will
n
ee
d
to
f
in
e
-
tu
n
e
o
r
ca
lib
r
ate
alg
o
r
ith
m
s
in
d
if
f
er
e
n
t
au
to
m
ated
t
o
o
ls
with
a
b
etter
u
n
d
e
r
s
tan
d
in
g
o
f
wh
at
is
in
v
o
lv
ed
in
th
e
class
if
icatio
n
o
f
tex
ts
b
ased
o
n
th
e
C
E
FR
g
u
id
elin
e.
Facto
r
s
r
elati
n
g
to
cu
ltu
r
al
n
o
r
m
s
o
f
d
if
f
er
e
n
t
co
m
m
u
n
ities
an
d
g
e
n
r
es
wi
ll
n
ee
d
t
o
b
e
tak
e
n
in
to
ac
co
u
n
t.
Fu
tu
r
e
t
o
o
l
d
e
v
elo
p
m
en
t
s
h
o
u
ld
ac
co
u
n
t
f
o
r
th
e
in
f
lu
en
ce
o
f
co
n
ten
t
a
n
d
g
en
r
e
o
n
C
E
FR
alig
n
m
en
t
to
im
p
r
o
v
e
ac
c
u
r
a
cy
.
R
esear
ch
er
s
an
d
p
r
ac
titi
o
n
er
s
s
h
o
u
ld
also
in
teg
r
ate
b
o
th
q
u
an
titativ
e
an
d
q
u
alitativ
e
m
eth
o
d
s
to
p
r
o
v
i
d
e
a
m
o
r
e
co
m
p
r
eh
e
n
s
iv
e
ass
ess
m
en
t
o
f
tex
t
d
if
f
icu
lty
.
A
d
d
r
ess
in
g
th
ese
is
s
u
e
s
will
h
elp
cr
ea
te
m
o
r
e
r
eliab
le
to
o
ls
th
at
b
etter
s
u
p
p
o
r
t
lan
g
u
ag
e
ed
u
c
atio
n
an
d
r
esear
ch
.
L
astl
y
,
o
n
e
o
f
th
e
m
ajo
r
im
p
licatio
n
s
o
f
th
is
s
tu
d
y
is
th
at
it
co
u
ld
in
itially
b
e
u
s
ed
to
co
n
f
ir
m
th
e
n
ee
d
f
o
r
a
m
o
r
e
q
u
alitativ
e
ap
p
r
o
ac
h
wh
en
d
o
in
g
tex
t d
if
f
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DATA AV
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[
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RE
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[
1
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R
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.
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.
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