segresnet-brats-mlx / native-run.json
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{
"schema_version": "medmlx.run.v1",
"model": "segresnet-brats",
"configuration": "MONAI brats_mri_segmentation (SegResNet, 4-channel MRI)",
"date": "2026-10-08",
"package": {
"name": "segresnet-mlx",
"path": "<repositories>/segresnet-mlx",
"git_revision": "40cbce54523632fbc8cdfc564a9cce48d8df3424",
"branch": "main",
"dirty": false,
"remote": "https://github.com/MedMLX/segresnet-mlx.git"
},
"environment": {
"machine": "MacBook Pro (2021), Apple M1 Max, 10-core CPU, 24-core GPU, 64 GB",
"macos": "27.0",
"python": "3.12.12",
"mlx_version": "0.32.3",
"device": "gpu"
},
"command": {
"entry_point": "segresnet_mlx.medmlx:run",
"kwargs": {
"bundle": "brats_mri_segmentation",
"weights_path": "<paper-repo>/work/runs/weights/segresnet-brats.safetensors",
"output_dir": "<paper-repo>/work/runs/segresnet-brats/out",
"t1c_path": "<home>/Documents/Codex/2026-10-08/https-drive-google-com-drive-folders/outputs/medmlx/datasets/qualification-2026-10-08/derived/msd-brain-channels/BRATS_001/T1gd.nii.gz",
"t1_path": "<home>/Documents/Codex/2026-10-08/https-drive-google-com-drive-folders/outputs/medmlx/datasets/qualification-2026-10-08/derived/msd-brain-channels/BRATS_001/T1w.nii.gz",
"t2_path": "<home>/Documents/Codex/2026-10-08/https-drive-google-com-drive-folders/outputs/medmlx/datasets/qualification-2026-10-08/derived/msd-brain-channels/BRATS_001/T2w.nii.gz",
"flair_path": "<home>/Documents/Codex/2026-10-08/https-drive-google-com-drive-folders/outputs/medmlx/datasets/qualification-2026-10-08/derived/msd-brain-channels/BRATS_001/FLAIR.nii.gz",
"overwrite": true
},
"invocation": "cd <repositories>/segresnet-mlx && .venv/bin/python <paper-repo>/work/runs/_harness/run_one.py segresnet_mlx.medmlx <kwargs.json> <run_result.json>",
"process": "fresh Python process per model"
},
"checkpoint": {
"path": "<paper-repo>/work/runs/weights/segresnet-brats.safetensors",
"sha256": "9044dcf3e2a82ef18f14d7abf507debbea52e14560c304b990a4c0e412bc9c30",
"source": "huggingface.co/MONAI/brats_mri_segmentation@370f7f9d models/model.pt (local HF cache)",
"source_sha256": "860ccb3f1c21c99d0410ad8a1ac4ef6b8fab60cec0a503b0ba42675741a750ae",
"registry_sha256_match": true,
"conversion": "segresnet_mlx.convert_checkpoint(spec=BUNDLES['brats_mri_segmentation'].spec)"
},
"inputs": [
{
"role": "t1c_path",
"path": "<home>/Documents/Codex/2026-10-08/https-drive-google-com-drive-folders/outputs/medmlx/datasets/qualification-2026-10-08/derived/msd-brain-channels/BRATS_001/T1gd.nii.gz",
"sha256": "96abcdbb541c4af37f03bef466eee5d11a3f91b9a1ea10b1a4a22cb38b7b3978",
"dataset": "MSD Task01 BrainTumour (training)",
"case_id": "BRATS_001",
"derivation": "channel split of imagesTr/BRATS_001.nii.gz (MSD order FLAIR,T1w,T1gd,T2w)"
},
{
"role": "t1_path",
"path": "<home>/Documents/Codex/2026-10-08/https-drive-google-com-drive-folders/outputs/medmlx/datasets/qualification-2026-10-08/derived/msd-brain-channels/BRATS_001/T1w.nii.gz",
"sha256": "740b0adfa8de83fcbdfa5cd5f14689f6d947120bfbf057fe82954c07477bb173",
"dataset": "MSD Task01 BrainTumour (training)",
"case_id": "BRATS_001",
"derivation": "channel split of imagesTr/BRATS_001.nii.gz (MSD order FLAIR,T1w,T1gd,T2w)"
},
{
"role": "t2_path",
"path": "<home>/Documents/Codex/2026-10-08/https-drive-google-com-drive-folders/outputs/medmlx/datasets/qualification-2026-10-08/derived/msd-brain-channels/BRATS_001/T2w.nii.gz",
"sha256": "8e2de5df0abd8b25ac1136c6570a6d03f2255107ef1265145b606f07acd1f1af",
"dataset": "MSD Task01 BrainTumour (training)",
"case_id": "BRATS_001",
"derivation": "channel split of imagesTr/BRATS_001.nii.gz (MSD order FLAIR,T1w,T1gd,T2w)"
},
{
"role": "flair_path",
"path": "<home>/Documents/Codex/2026-10-08/https-drive-google-com-drive-folders/outputs/medmlx/datasets/qualification-2026-10-08/derived/msd-brain-channels/BRATS_001/FLAIR.nii.gz",
"sha256": "7571148ce691dccff5a84109091f43385b7c069a99cd7a967b2002aaeec64cdd",
"dataset": "MSD Task01 BrainTumour (training)",
"case_id": "BRATS_001",
"derivation": "channel split of imagesTr/BRATS_001.nii.gz (MSD order FLAIR,T1w,T1gd,T2w)"
}
],
"outputs": {
"mask": {
"path": "<paper-repo>/work/runs/segresnet-brats/out/brats_mri_segmentation_mask.nii.gz",
"sha256": "ce7f2ca25eeb2e1dea09e748dfdf1ec666a16296bc523a0b537608575ed5dcd6",
"label_voxel_counts": {
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"1": 27348,
"2": 74690,
"4": 34329
}
},
"details": {
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],
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],
"sliding_window": {
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"overlap": 0.5
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"preprocess": 0.1134,
"inference": 1.4535,
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}
}
},
"checks": [
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"name": "mask_reopens",
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"detail": {
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}
},
{
"name": "finite_integer_labels",
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"detail": null
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{
"name": "shape_matches_input",
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"detail": {
"input": [
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],
"mask": [
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}
},
{
"name": "affine_matches_input",
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"detail": {
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},
{
"name": "labels_in_expected_set",
"result": "pass",
"detail": {
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"allowed": [
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},
{
"name": "foreground_nonempty",
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"detail": {
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},
{
"name": "required_labels_present",
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"detail": {
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}
},
{
"name": "tumor_overlaps_annotated_region",
"result": "pass",
"detail": {
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}
}
],
"duration_s": 2.271,
"timing_boundary": "wall clock around the single run() call: weight loading, preprocessing, MLX inference and export; interpreter start-up and package import excluded; one run, no warmup",
"mlx_peak_gb": 6.954,
"memory_definition": "mx.get_peak_memory() after mx.reset_peak_memory() immediately before run(); decimal GB",
"panel": "paper/figures/runs/segresnet-brats.png",
"status": "success",
"failure_cause": null,
"notes": "BRATS_001 is training-exposed MSD data; overlap with the MSD label is a sanity check, not an accuracy claim.",
"key_check": "labels [1, 2, 4]; whole_tumor_dice_vs_msd_label_informational = 0.8897"
}