Table:
literacy
numeracy

model 1
model 2
model 3
model 1
model 2
model 3

predicted probability

higher skill level

off-reserve first nations
0.638
0.660
0.658
0.655
0.678
0.681

metis
0.583
0.592
0.588
0.604
0.614
0.611

non-aboriginal
0.710
0.694
0.698
0.710
0.692
0.699

lower skill level

off-reserve first nations
0.347
0.463
0.462
0.390
0.493
0.486

metis
0.354
0.490
0.483
0.376
0.494
0.483

non-aboriginal
0.421
0.535
0.534
0.468
0.567
0.561

Analyze the provided table and extract the contents of specified rows or columns, identified by row or column indices. Provide the cells in each row or column in the JSON structure, using the format {"row_id/column_id":"<row or column index>", "cell_list":"<a list of cells in this row/column>"}.
Target rows or columns:
column 1
row 3
column 5
row 6

The extracted row or column contents are listed below.
For column 1: {"column_id": "1", "cell_list": ['', '', '', 'higher skill level', 'off-reserve first nations', 'metis', 'non-aboriginal', 'lower skill level', 'off-reserve first nations', 'metis', 'non-aboriginal']}
For row 3: {"row_id": "3", "cell_list": ['', 'predicted probability', '', '', '', '', '']}
For column 5: {"column_id": "5", "cell_list": ['numeracy', 'model 1', '', '', '0.655', '0.604', '0.710', '', '0.390', '0.376', '0.468']}
For row 6: {"row_id": "6", "cell_list": ['metis', '0.583', '0.592', '0.588', '0.604', '0.614', '0.611']}