{
  "scope": "deterministic integrity comparison of existing data; no AL, docking, model training, or cache replacement",
  "cache_sha256": "10b4a50f5cfc3de000ab06d0b8112146486e63571ad9db252455dd5af3976a91",
  "raw_id_index_sha256": "7e265af1318119a7c8e2086fbf4bc2786143d825b68479e6bd83ede46e4bf294",
  "ligand_sha256": "ad74c18a2560f0c4577a045c22582ce37a1d1827ec05bce48bd1cd1111c54b0c",
  "producer_reference": "dal_toolbox_design2/run_dal_toolbox_design2.py functions normalize_features, random_project, load_ligand_features, pooled_graph_feature, build_complex_features",
  "shape": [
    3179,
    256
  ],
  "numpy_version": "2.3.5",
  "projection_seed": 0,
  "absolute_tolerance": 2e-05,
  "relative_tolerance": 2e-05,
  "maximum_absolute_difference": 2.193450927734375e-05,
  "root_mean_square_difference": 2.3208026557708418e-06,
  "matching_values": 813824,
  "total_values": 813824,
  "matching_rows": 3179,
  "total_rows": 3179,
  "bitwise_numeric_equal": false,
  "passed": true,
  "note": "NumPy float32 node pooling can differ in rounding from original PyTorch pooling; all comparisons are explicitly quantified.",
  "elapsed_seconds": 8.6,
  "packaged_producer_excerpt": "provenance/historical_acquisition_source/feature_builder_excerpt.py.txt",
  "packaged_producer_provenance": "provenance/historical_acquisition_source/feature_builder_provenance.json"
}