[
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    "arch": "c3d",
    "anatomy": "source-domain",
    "regime": "pretrained",
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    "source_size_bytes": 129481303,
    "sha256": "b215969e57733cc6699d17a9d23f20dde8411971f2662fd114c66ee0c25befef",
    "note": "Source-domain model trained on the public 8-channel dose dataset. Starting point for c3d_finetuned.pt and pancreas_c3d_finetuned.pt."
  },
  {
    "file": "c3d_finetuned.pt",
    "arch": "c3d",
    "anatomy": "han",
    "regime": "finetuned",
    "in_channels": 5,
    "channel_spec": "han_5ch",
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    "sha256": "73679f45b10104d96b8a28f90024f3f92be9a40e8bc733fa02e18d31825f43be",
    "note": "Fine-tuned from c3d_pretrained.pt on head-and-neck data; Adam lr 3e-5, cosine schedule, 275 epochs."
  },
  {
    "file": "c3d_fromscratch.pt",
    "arch": "c3d",
    "anatomy": "han",
    "regime": "fromscratch",
    "in_channels": 5,
    "channel_spec": "han_5ch",
    "scale_out": 7.5,
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    "sha256": "7e7df38af255dcb9b8621b058f1265a1c6946c32c51edf501e4c0b628e94208e",
    "note": "Same architecture and schedule trained from random init; Adam lr 1e-4. The no-transfer baseline."
  },
  {
    "file": "mednext_pretrained.pt",
    "arch": "mednext",
    "anatomy": "source-domain",
    "regime": "pretrained",
    "in_channels": 8,
    "channel_spec": "source_8ch",
    "scale_out": 7.5,
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    "source_size_bytes": 42184734,
    "sha256": "75c971ae3a35e14fa6e1667b829f367f07b5d8c57404871d62610c38c86f1b70",
    "note": "Source-domain MedNeXt-B trained on the public 8-channel dose dataset."
  },
  {
    "file": "mednext_finetuned.pt",
    "arch": "mednext",
    "anatomy": "han",
    "regime": "finetuned",
    "in_channels": 5,
    "channel_spec": "han_5ch",
    "scale_out": 7.5,
    "eval_clip_factor": 1.2,
    "num_parameters": 10526402,
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    "source_size_bytes": 168792326,
    "sha256": "f397b9bc4ec257f07b798f55adf8143085fc3f236dccc2a043de084c9260694e",
    "note": "Fine-tuned from mednext_pretrained.pt on head-and-neck data."
  },
  {
    "file": "mednext_fromscratch.pt",
    "arch": "mednext",
    "anatomy": "han",
    "regime": "fromscratch",
    "in_channels": 5,
    "channel_spec": "han_5ch",
    "scale_out": 7.5,
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    "source_size_bytes": 168793926,
    "sha256": "e1e041424d496e1241b56f9b73b79fde0bb5c473e4299db5bf34609904ab463c",
    "note": "MedNeXt-B trained from random init. The no-transfer baseline."
  },
  {
    "file": "swinunetr_pretrained.pt",
    "arch": "swinunetr",
    "anatomy": "source-domain",
    "regime": "pretrained",
    "in_channels": 8,
    "channel_spec": "source_8ch",
    "scale_out": 7.5,
    "eval_clip_factor": 1.2,
    "num_parameters": 291356139,
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    "size_bytes": 1169245779,
    "source": "Pretrained/SwinUNETR_L_128x128x160/best_val.pth",
    "source_size_bytes": 1169258908,
    "sha256": "edca3e20d8a6f1a00b4d3c6dfbf19e67c4f89b3fbd769c2ed9bae7ce51520160",
    "note": "Source-domain SwinUNETR-L trained on the public 8-channel dose dataset."
  },
  {
    "file": "swinunetr_finetuned.pt",
    "arch": "swinunetr",
    "anatomy": "han",
    "regime": "finetuned",
    "in_channels": 5,
    "channel_spec": "han_5ch",
    "scale_out": 7.5,
    "eval_clip_factor": 1.2,
    "num_parameters": 291345771,
    "num_tensors": 167,
    "size_bytes": 1169204072,
    "source": "Output/SwinUNETR_L/Finetune/best_val_evaluation_index.pkl",
    "source_size_bytes": 4654279265,
    "sha256": "e92c795b3792094fa881a8f7a7ef4a03a411454f78026351ea38fe5b0632204e",
    "note": "Fine-tuned from swinunetr_pretrained.pt on head-and-neck data."
  },
  {
    "file": "swinunetr_fromscratch.pt",
    "arch": "swinunetr",
    "anatomy": "han",
    "regime": "fromscratch",
    "in_channels": 5,
    "channel_spec": "han_5ch",
    "scale_out": 7.5,
    "eval_clip_factor": 1.2,
    "num_parameters": 291345771,
    "num_tensors": 167,
    "size_bytes": 1169204414,
    "source": "Output/SwinUNETR_L/FromScratch/best_val_evaluation_index.pkl",
    "source_size_bytes": 4654274081,
    "sha256": "6981fa28668ab6efc1f5450eea8921b2c6477803eff8582911c6e4ff8ec4881f",
    "note": "SwinUNETR-L trained from random init. The no-transfer baseline."
  },
  {
    "file": "pancreas_c3d_pretrained.pt",
    "arch": "c3d",
    "anatomy": "source-domain",
    "regime": "pretrained",
    "in_channels": 8,
    "channel_spec": "source_8ch",
    "scale_out": 5.5,
    "eval_clip_factor": 1.2,
    "num_parameters": 32353106,
    "num_tensors": 172,
    "size_bytes": 129471450,
    "source": "Pretrained/C3D_128x128x160/best_val.pth",
    "source_size_bytes": 129481303,
    "sha256": "aa51c8851a2eb0f74b0e59c8a202e57ceee1013abb2274bf7b52e1a623b926f4",
    "note": "Byte-identical weights to c3d_pretrained.pt; duplicated so the pancreas set is self-contained. Only scale_out differs (5.5 for pancreas)."
  },
  {
    "file": "pancreas_c3d_finetuned.pt",
    "arch": "c3d",
    "anatomy": "pancreas",
    "regime": "finetuned",
    "in_channels": 5,
    "channel_spec": "pancreas_5ch",
    "scale_out": 5.5,
    "eval_clip_factor": 1.2,
    "num_parameters": 32349218,
    "num_tensors": 172,
    "size_bytes": 129455658,
    "source": "Output/Pancreas/PancC3D/FineTune_v5/best_val_evaluation_index.pkl",
    "source_size_bytes": 517882405,
    "sha256": "36d4b7369e4221cf86e3c06947c98fa8e96d1d50381d362933a13ec0fdca777f",
    "note": "Fine-tuned directly from the source-domain pretrained C3D onto pancreas VMAT data -- NOT from the head-and-neck model."
  },
  {
    "file": "pancreas_c3d_fromscratch.pt",
    "arch": "c3d",
    "anatomy": "pancreas",
    "regime": "fromscratch",
    "in_channels": 5,
    "channel_spec": "pancreas_5ch",
    "scale_out": 5.5,
    "eval_clip_factor": 1.2,
    "num_parameters": 32349218,
    "num_tensors": 172,
    "size_bytes": 129455946,
    "source": "Output/Pancreas/PancC3D/FromScratch/best_val_evaluation_index.pkl",
    "source_size_bytes": 517899237,
    "sha256": "e80eb22116f022fb170094f5eae29529275838098fe2d0490f92d721f3a98436",
    "note": "C3D trained from random init on pancreas VMAT data. The no-transfer baseline."
  }
]