Table:
broad field
2017
2018
2019
percent change 2017-19

all surveyed fields
28180
29284
30349
7.7

male
16580
17468
17980
8.4

female
11600
11816
12369
6.6

science and engineering
20542
21848
22728
10.6

science
17268
18278
18819
9

agricultural sciences
496
565
645
30

biological and biomedical sciences
8203
8250
8229
0.3

computer and information sciences
476
515
510
7.1

geosciences, atmospheric sciences, and ocean sciences
1794
2106
2177
21.3

mathematics and statistics
240
266
305
27.1

multidisciplinary and interdisciplinary studies
806
832
820
1.7

natural resources and conservation
364
580
582
59.9

physical sciences
2871
3056
3316
15.5

psychology
494
507
576
16.6

social sciences
1524
1601
1659
8.9

engineering
3274
3570
3909
19.4

bioengineering and biomedical engineering
415
440
492
18.6

chemical engineering
281
257
328
16.7

civil engineering
422
414
492
16.6

electrical, electronics, and communications engineering
557
588
637
14.4

engineering science, mechanics, and physics
200
220
186
-7

industrial and manufacturing engineering
119
105
137
15.1

mechanical engineering
458
489
531
15.9

metallurgical and materials engineering
181
215
242
33.7

other engineeringa
641
842
864
34.8

health
7638
7436
7621
-0.2

clinical medicine
6448
6159
6273
-2.7

other health
1190
1277
1348
13.3

Extract the cells' contents in the 4th column in this table. The cells in a column should be presented in the JSON format of {"column_id":"<column index>", "cell_list":"<a list of cells in this column>"}, e.g., {"column_id":"3", "cell_list": ["xxx", "yyy", "zzz"]}.

The target cell values of the 4th column: {"column_id": "4", "cell_list": ['2019', '30349', '17980', '12369', '22728', '18819', '645', '8229', '510', '2177', '305', '820', '582', '3316', '576', '1659', '3909', '492', '328', '492', '637', '186', '137', '531', '242', '864', '7621', '6273', '1348']}