{
  "schema_version": "medmlx.reference.v1",
  "model": "segresnet-brats",
  "date": "2026-10-12",
  "case": {
    "dataset": "MSD Task01 BrainTumour (training)",
    "case_id": "BRATS_001",
    "input_sha256": {
      "t1c_path": "96abcdbb541c4af37f03bef466eee5d11a3f91b9a1ea10b1a4a22cb38b7b3978",
      "t1_path": "740b0adfa8de83fcbdfa5cd5f14689f6d947120bfbf057fe82954c07477bb173",
      "t2_path": "8e2de5df0abd8b25ac1136c6570a6d03f2255107ef1265145b606f07acd1f1af",
      "flair_path": "7571148ce691dccff5a84109091f43385b7c069a99cd7a967b2002aaeec64cdd"
    }
  },
  "original": {
    "code": "MONAI / MONAI model-zoo brats_mri_segmentation",
    "version_or_commit": "MONAI 1.6.0 (eccefc57550b111ed781d82249dfe77872a0e918); model-zoo db9eeeef7ba64ce2ced0230d9bd4c524f69b7f0c",
    "device": "cpu",
    "precision": "float32 (AMP disabled on CPU)",
    "checkpoint_sha256": "860ccb3f1c21c99d0410ad8a1ac4ef6b8fab60cec0a503b0ba42675741a750ae",
    "command": "<paper-repo>/work/reference/segresnet-brats/.venv/bin/python -I -B <paper-repo>/benchmarks/reference/segresnet-brats.py"
  },
  "mlx": {
    "run_record": "results/runs/segresnet-brats.json",
    "output_path": "<paper-repo>/work/runs/segresnet-brats/out/brats_mri_segmentation_mask.nii.gz",
    "output_sha256": "ce7f2ca25eeb2e1dea09e748dfdf1ec666a16296bc523a0b537608575ed5dcd6"
  },
  "comparison": {
    "metric": "minimum_per_label_dice",
    "value": 1.0,
    "per_label": {
      "0": {
        "dice": 1.0,
        "original_voxels": 8791633,
        "mlx_voxels": 8791633
      },
      "1": {
        "dice": 1.0,
        "original_voxels": 27348,
        "mlx_voxels": 27348
      },
      "2": {
        "dice": 1.0,
        "original_voxels": 74690,
        "mlx_voxels": 74690
      },
      "4": {
        "dice": 1.0,
        "original_voxels": 34329,
        "mlx_voxels": 34329
      }
    },
    "threshold": 0.99,
    "differing_voxel_count": 0,
    "result": "pass"
  },
  "notes": "Pinned original MONAI CPU SegResNet and full bundle preprocessing, SlidingWindowInferer and postprocessing. Channel order T1gd,T1w,T2w,FLAIR is exactly the recorded MLX order; case.input_sha256 contains each recorded role's checksum. Original model.pt was found in the recorded HF snapshot 370f7f9d062745fbac445e7fe6d6616d35df04ec and matches source_sha256. Sigmoid, inverse transform, threshold 0.5 and original BraTS label precedence 4 > 1 > 2 used. Dice covers every label including background; all MRI grids and both mask affines/shapes match. AMP is disabled for CPU float32 inference. Raw outputs, source configuration, dependency versions and log: work/reference/segresnet-brats/. Training-exposed MSD case; this is reproducibility evidence, not an accuracy study.",
  "failure": null
}