{
  "schema_version": 1,
  "kind": "curated_evidence_not_full_reproduction_bundle",
  "source_snapshot": "results\\smoke\\092946-908502-8a37f1\\runs\\2026-10-29\\114406-974802-3a85a8",
  "source_revision": null,
  "source_revision_note": "No git revision was available in the saved run records.",
  "dataset": {
    "name": "wine",
    "loader": "sklearn.datasets.load_wine",
    "source": "https://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_wine.html",
    "task": "classification",
    "source_rows": 178,
    "features": 13,
    "classes": 3
  },
  "execution": {
    "run_type": "smoke",
    "cv": "holdout",
    "split_seed": 0,
    "model_seed": 0,
    "jobs": 1,
    "device_requested": "cuda",
    "n_train_per_fit": 124,
    "n_test_per_fit": 32,
    "prediction_shape_per_fit": [32, 3],
    "platform_family": "Windows",
    "python": "3.13.4",
    "gpu": "NVIDIA GeForce RTX 5070 Ti",
    "torch": "2.11.0+cu128",
    "backends": ["histgb", "lightgbm", "tabfm", "kumo_tabular"],
    "effective_devices": {
      "histgb": "cpu",
      "lightgbm": "cpu",
      "tabfm": "cuda",
      "kumo_tabular": "cuda"
    }
  },
  "observation": {
    "correct_predictions_per_backend": 32,
    "accuracy_per_backend": 1.0,
    "distinct_test_rows": 32,
    "backend_pairs": 6,
    "shared_rows_per_pair": 32,
    "pair_row_observations": 192,
    "class_disagreements": 0,
    "disagreement_definition": "Different argmax predicted classes on the same original test row.",
    "probability_identity_claimed": false
  },
  "verification": [
    "Each source record had no error/refused result and recorded smoke holdout, seed 0, jobs 1.",
    "Training/test counts and effective devices matched the portable CSV.",
    "Each probability array had shape (32, 3) and finite values.",
    "Accuracy was recomputed from argmax predictions against the saved targets.",
    "Test indices contained 32 unique original row positions.",
    "All six backend pairs had zero argmax disagreements on the 32 shared rows.",
    "SHA-256 was computed over the original archived file bytes."
  ],
  "source_sha256": {
    "wine\\histgb_ss0_ms0.json": "a05a06653c1531ee453ea62ce32e610f9ff1b07115b8c35a16852def0dac0068",
    "wine\\histgb_ss0_ms0.pred.npy": "f3714e32f99bd74397c6fae78c4eaa5d8d7152adf1eee84cd6588dd5f9bf424a",
    "wine\\lightgbm_ss0_ms0.json": "c445cf6058876d32149eb200f13b5a4c535790b8a631e690b91ab2585115cbe9",
    "wine\\lightgbm_ss0_ms0.pred.npy": "d6c091cf282d2b64aeb0cc3175021f744cff0d2d935987bba6f66d99e1b135fc",
    "wine\\tabfm_ss0_ms0.json": "6d1995ff14097b79b77ae19a885da65069a3ecd6e11f8e4fb29c95b50139b90b",
    "wine\\tabfm_ss0_ms0.pred.npy": "940ec69305d59636fbc6335412d2fe904e44558586b86586b3682561aadfe6b9",
    "wine\\kumo_tabular_ss0_ms0.json": "fb7844ca02fa4ad54cb40b7511b228496d75fea55030161cd952cf50b38ba2e9",
    "wine\\kumo_tabular_ss0_ms0.pred.npy": "f76e2b0cde10e9a990350fc740907ba7ae5376a9f516f4da538f97ccf0dcbe77",
    "wine\\idx_test_ss0.npy": "8dd5d6d01e0d01f51da0568650cfaea33597572e153511615515d2df93e6d0be",
    "wine\\y_test_ss0.npy": "0f116d92eb3d9c70771a8ea04e1c143c67831a5194f58b946ed2a777e5d5d9ec"
  },
  "limits": [
    "This is a setup smoke check, not a full-data or multi-dataset benchmark.",
    "The 192 pair-row observations reuse only 32 distinct test rows.",
    "All-correct predictions on this sample do not establish population-perfect accuracy.",
    "Predicted-class agreement does not imply identical probability estimates.",
    "CPU and CUDA execution are mixed; no controlled speed/resource ranking is claimed.",
    "The source snapshot is local and ignored by git, not included in this curated bundle.",
    "Hashes identify bytes if original files are supplied; they do not prove execution or reconstruct files.",
    "The bundle does not contain original inputs, prediction arrays, model weights, or a full environment lock."
  ]
}