{
  "runtime": "3.12.14",
  "shape": [
    3,
    4
  ],
  "raw_records": [
    [
      0,
      1,
      3
    ],
    [
      0,
      1,
      4
    ],
    [
      0,
      3,
      0
    ],
    [
      2,
      0,
      2
    ]
  ],
  "csr_contract": {
    "data": [
      3,
      4,
      0,
      2
    ],
    "indices": [
      1,
      1,
      3,
      0
    ],
    "indptr": [
      0,
      3,
      3,
      4
    ]
  },
  "dense_source": [
    [
      0,
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      0,
      0
    ],
    [
      0,
      0,
      0,
      0
    ],
    [
      2,
      0,
      0,
      0
    ]
  ],
  "canonical_records": [
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      0,
      1,
      7
    ],
    [
      0,
      3,
      0
    ],
    [
      2,
      0,
      2
    ]
  ],
  "square_before_merge": [
    [
      0,
      25,
      0,
      0
    ],
    [
      0,
      0,
      0,
      0
    ],
    [
      4,
      0,
      0,
      0
    ]
  ],
  "square_after_merge": [
    [
      0,
      49,
      0,
      0
    ],
    [
      0,
      0,
      0,
      0
    ],
    [
      4,
      0,
      0,
      0
    ]
  ],
  "square_dense_oracle": [
    [
      0,
      49,
      0,
      0
    ],
    [
      0,
      0,
      0,
      0
    ],
    [
      4,
      0,
      0,
      0
    ]
  ],
  "plus_one_stored_only": [
    [
      0,
      8,
      0,
      1
    ],
    [
      0,
      0,
      0,
      0
    ],
    [
      3,
      0,
      0,
      0
    ]
  ],
  "plus_one_dense_oracle": [
    [
      1,
      8,
      1,
      1
    ],
    [
      1,
      1,
      1,
      1
    ],
    [
      3,
      1,
      1,
      1
    ]
  ],
  "f_zero": {
    "square": 0,
    "plus_one": 1
  },
  "scipy_executed": false,
  "scope": "Only12 authored cells and record-sum contract. f(0)=0 alone is insufficient before duplicate merging for nonlinear transforms; no densification advice for large data."
}