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Unnamed: 0
int64
1
984
treat
int64
0
1
bw
int64
540
2.5k
b.head
float64
20
36
preterm
int64
2
15
birth.o
int64
1
4
nnhealth
int64
17
137
momage
int64
14
43
sex
int64
0
1
twin
int64
0
1
b.marr
int64
0
1
mom.lths
int64
0
1
mom.hs
int64
0
1
mom.scoll
int64
0
1
cig
int64
0
1
first
int64
1
2
booze
int64
0
1
drugs
int64
0
1
work.dur
int64
0
1
prenatal
int64
0
1
ark
int64
0
1
ein
int64
0
1
har
int64
0
1
mia
int64
0
1
pen
int64
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1
tex
int64
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1
was
int64
0
1
momwhite
int64
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1
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int64
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1
momhisp
int64
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1
1
1
1,559
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112
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1,984
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99
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23
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125
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31
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1,400
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92
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730
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870
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12
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45
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1,510
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10
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100
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1
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46
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2,360
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103
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47
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2,500
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48
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1,880
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4
109
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1
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49
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2,220
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1
1
1
1
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50
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2,490
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2
80
24
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0
1
0
1
0
1
1
1
1
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1
1
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51
0
2,350
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4
99
21
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1
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1
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1
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1
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1
1
0
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0
53
1
910
25
12
1
84
22
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0
1
0
1
0
1
2
0
1
1
1
1
0
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54
1
2,445
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3
98
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1
1
1
1
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56
1
2,180
31
6
1
87
29
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0
1
1
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0
0
2
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1
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1
1
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58
1
1,786
31
8
2
42
25
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0
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0
1
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1
1
1
1
0
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1
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59
0
2,160
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6
2
118
25
1
0
1
0
1
0
0
1
0
1
1
1
1
0
0
0
0
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0
1
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0
60
0
1,928
30
8
2
89
34
1
0
1
0
0
1
0
1
0
1
1
1
1
0
0
0
0
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0
1
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0
61
0
1,750
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5
2
99
17
1
1
0
1
0
0
0
1
0
1
0
1
1
0
0
0
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0
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1
0
62
0
1,590
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10
3
83
19
1
0
1
1
0
0
1
1
0
1
0
1
1
0
0
0
0
0
0
1
0
0
63
1
2,350
32
6
1
113
18
1
0
0
1
0
0
1
2
0
1
0
1
1
0
0
0
0
0
0
1
0
0
64
1
2,250
33
7
2
99
19
0
0
0
1
0
0
1
1
0
1
0
1
1
0
0
0
0
0
0
1
0
0
65
0
1,890
31
9
1
81
20
1
0
1
0
1
0
0
2
0
1
1
1
1
0
0
0
0
0
0
1
0
0
66
0
2,410
31
6
4
65
40
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0
1
0
1
0
0
1
0
1
0
1
1
0
0
0
0
0
0
1
0
0
67
1
2,500
33
6
2
91
25
1
0
1
1
0
0
0
1
0
1
1
1
1
0
0
0
0
0
0
1
0
0
68
0
2,353
31
6
2
99
28
0
0
0
0
0
1
1
1
0
1
1
1
1
0
0
0
0
0
0
0
1
0
70
0
1,960
31
5
2
109
24
0
0
1
0
1
0
0
1
0
1
0
1
1
0
0
0
0
0
0
0
1
0
72
0
920
25
13
1
84
19
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0
0
0
0
1
1
2
1
1
1
1
1
0
0
0
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1
0
73
0
2,300
33
5
1
110
22
0
0
0
0
0
1
1
2
0
1
1
1
1
0
0
0
0
0
0
1
0
0
74
1
1,985
29
5
1
108
24
1
0
1
0
0
1
1
2
0
1
1
1
1
0
0
0
0
0
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1
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0
76
1
1,740
30
7
4
127
26
1
0
0
1
0
0
1
1
0
1
0
1
1
0
0
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1
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77
0
1,970
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117
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1
0
0
0
1
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0
1
0
1
1
1
1
0
0
0
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1
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79
0
2,390
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2
105
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1
0
0
1
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0
0
1
0
1
0
1
1
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0
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80
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1,750
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119
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0
0
1
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0
0
2
0
1
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1
1
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81
1
1,970
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107
33
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0
1
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0
2
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1
1
1
1
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82
0
2,070
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93
21
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1
0
0
1
0
1
1
1
1
0
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1
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83
0
1,400
28
9
2
107
18
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0
0
1
0
0
0
1
0
1
0
1
1
0
0
0
0
0
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1
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84
0
1,360
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3
117
26
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0
1
1
0
0
1
1
1
1
1
0
1
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85
0
2,155
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1
110
28
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0
1
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1
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2
0
1
1
1
1
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87
0
1,190
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4
118
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0
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1
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1
1
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0
1,950
31
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103
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1
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1
1
1
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90
0
1,240
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3
100
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0
1
1
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1
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1
1
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91
0
1,410
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1
93
24
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0
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0
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0
2
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1
1
1
1
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94
0
2,270
31
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2
117
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0
1
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1
1
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1
1
1
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95
0
1,840
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72
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96
1
1,670
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1
113
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97
1
2,400
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3
63
25
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1
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1
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98
1
2,230
33
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2
100
23
1
1
1
0
1
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1
1
0
1
1
1
1
0
0
0
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1
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100
0
1,520
29
9
2
99
20
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1
0
1
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0
1
0
1
1
1
1
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0
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0
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0
101
0
1,070
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10
1
85
19
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0
1
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0
1
2
1
1
1
1
1
0
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104
1
2,200
34
7
1
108
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1
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1
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0
1,790
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106
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67
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1,420
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86
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109
0
1,730
29
9
3
90
24
0
0
0
0
0
1
0
1
0
1
1
1
1
0
0
0
0
0
0
0
1
0
110
1
1,560
27
7
1
107
17
0
0
0
1
0
0
1
2
0
1
1
1
1
0
0
0
0
0
0
1
0
0
111
0
1,730
28
6
1
122
20
1
0
0
1
0
0
1
2
0
1
0
1
1
0
0
0
0
0
0
0
1
0
112
1
1,580
30
6
1
124
15
0
0
0
1
0
0
1
2
0
1
0
1
1
0
0
0
0
0
0
1
0
0
114
0
2,325
32
3
1
98
19
1
0
1
0
1
0
1
2
0
1
1
1
1
0
0
0
0
0
0
1
0
0
115
0
1,580
29
10
2
87
23
0
1
1
0
1
0
0
1
0
1
1
1
1
0
0
0
0
0
0
1
0
0
116
0
2,296
32
7
1
72
35
0
0
1
0
0
0
1
2
0
1
1
1
1
0
0
0
0
0
0
1
0
0
117
1
2,417
32
6
3
96
29
1
0
1
0
0
0
0
1
0
1
0
1
1
0
0
0
0
0
0
1
0
0
118
0
1,210
27
12
1
86
25
0
0
1
0
0
1
0
2
0
1
1
1
1
0
0
0
0
0
0
1
0
0
119
0
1,570
30
6
4
95
23
0
1
0
1
0
0
1
1
1
1
1
1
1
0
0
0
0
0
0
0
1
0
120
0
2,190
32
5
2
116
19
0
0
0
1
0
0
1
1
1
1
0
0
1
0
0
0
0
0
0
0
1
0
121
0
2,001
32
5
1
105
37
0
1
0
0
0
0
0
2
0
1
1
1
1
0
0
0
0
0
0
0
1
0
122
0
2,200
31
4
2
121
21
0
0
1
0
1
0
0
1
0
1
0
1
1
0
0
0
0
0
0
0
1
0
123
0
2,000
31
5
3
122
28
1
0
0
1
0
0
1
1
0
1
1
1
1
0
0
0
0
0
0
1
0
0
124
0
1,990
30
7
1
127
17
0
0
0
1
0
0
1
2
0
1
1
1
1
0
0
0
0
0
0
1
0
0
126
0
2,120
31
6
2
85
24
0
0
1
0
0
1
0
1
0
1
1
1
1
0
0
0
0
0
0
0
1
0

This dataset contains the necesary data to reproduce the paper

Tec et al. (2024). Causal Estimation of Exposure Shifts with Neural Networks. In: KDD.

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