30 vs 120 epoch comparison · same six datasets / 1,227 weak label targets; exclusion verified in all 70 checkpoints.
14 datasets · 6 designs · 0 scored records
Training status: completed_with_weak_training · 280 trained prediction records · 63 folds with epoch losses
PNG results, losses & training diagnosis · CAD / scan / label / model-input visualizer
— = no valid score. Diagnostic and training-fit outputs are separate from unseen-design evaluation.
Training fit and held-out-design agreement are shown separately. These targets are not independently reviewed accuracy.
Bold marks the best value in each metric column within its table, including ties. Lower BCE is better; higher AP and IoU are better.
train_all| Model | Datasets | BCE ↓ | AP ↑ | IoU ↑ |
|---|---|---|---|---|
| cnn2d_unet | 6 | 0.0211 | 0.9451 | 0.8667 |
| dgcnn | 6 | 0.1529 | 0.1654 | 0.0000 |
| fno2d | 6 | 0.0258 | 0.9411 | 0.8622 |
| gaussian_process | 6 | 0.1292 | 0.7332 | 0.4473 |
| meshgraphnet | 6 | 0.1562 | 0.0916 | 0.0000 |
| physics_risk_gnn | 6 | 0.1535 | 0.1393 | 0.0000 |
| pointnet | 6 | 0.1601 | 0.0778 | 0.0000 |
| tabular_mlp | 6 | 0.1576 | 0.0815 | 0.0000 |
| unet3d | 6 | 0.0276 | 0.9333 | 0.8093 |
| uvnet | 6 | 0.1542 | 0.1476 | 0.0000 |
leave_one_design_out| Model | Datasets | BCE ↓ | AP ↑ | IoU ↑ |
|---|---|---|---|---|
| cnn2d_unet | 6 | 0.4378 | 0.1213 | 0.0000 |
| dgcnn | 6 | 0.1965 | 0.0503 | 0.0000 |
| fno2d | 6 | 0.7015 | 0.0434 | 0.0000 |
| gaussian_process | 6 | 0.4530 | 0.0745 | 0.0000 |
| meshgraphnet | 6 | 0.2085 | 0.0690 | 0.0000 |
| physics_risk_gnn | 6 | 0.2060 | 0.0372 | 0.0000 |
| pointnet | 6 | 0.1967 | 0.0517 | 0.0000 |
| tabular_mlp | 6 | 0.1911 | 0.0501 | 0.0000 |
| unet3d | 6 | 0.4631 | 0.0367 | 0.0000 |
| uvnet | 6 | 0.2043 | 0.2203 | 0.0889 |
| Model | Protocol | Scored datasets | MAE | RMSE | AP | IoU | Dice |
|---|---|---|---|---|---|---|---|
| cnn2d_unet | diagnostic | 0 | — | — | — | — | — |
| cnn2d_unet | leave_one_design_out | 0 | — | — | — | — | — |
| cnn2d_unet | train_all | 0 | — | — | — | — | — |
| dgcnn | diagnostic | 0 | — | — | — | — | — |
| dgcnn | leave_one_design_out | 0 | — | — | — | — | — |
| dgcnn | train_all | 0 | — | — | — | — | — |
| fno2d | diagnostic | 0 | — | — | — | — | — |
| fno2d | leave_one_design_out | 0 | — | — | — | — | — |
| fno2d | train_all | 0 | — | — | — | — | — |
| gaussian_process | diagnostic | 0 | — | — | — | — | — |
| gaussian_process | leave_one_design_out | 0 | — | — | — | — | — |
| gaussian_process | train_all | 0 | — | — | — | — | — |
| meshgraphnet | diagnostic | 0 | — | — | — | — | — |
| meshgraphnet | leave_one_design_out | 0 | — | — | — | — | — |
| meshgraphnet | train_all | 0 | — | — | — | — | — |
| physics_risk_gnn | diagnostic | 0 | — | — | — | — | — |
| physics_risk_gnn | leave_one_design_out | 0 | — | — | — | — | — |
| physics_risk_gnn | train_all | 0 | — | — | — | — | — |
| pointnet | diagnostic | 0 | — | — | — | — | — |
| pointnet | leave_one_design_out | 0 | — | — | — | — | — |
| pointnet | train_all | 0 | — | — | — | — | — |
| sparse_unet | diagnostic | 0 | — | — | — | — | — |
| sparse_unet | leave_one_design_out | 0 | — | — | — | — | — |
| sparse_unet | train_all | 0 | — | — | — | — | — |
| tabular_mlp | diagnostic | 0 | — | — | — | — | — |
| tabular_mlp | leave_one_design_out | 0 | — | — | — | — | — |
| tabular_mlp | train_all | 0 | — | — | — | — | — |
| unet3d | diagnostic | 0 | — | — | — | — | — |
| unet3d | leave_one_design_out | 0 | — | — | — | — | — |
| unet3d | train_all | 0 | — | — | — | — | — |
| uvnet | diagnostic | 0 | — | — | — | — | — |
| uvnet | leave_one_design_out | 0 | — | — | — | — | — |
| uvnet | train_all | 0 | — | — | — | — | — |
Individual scores · Detailed predictions/targets · Data and code provenance
{'evaluation_protocols': {'leave_one_design_out': 'All records sharing a design-file SHA256 are held out together. Fit and preprocessing statistics use training records only.', 'per_design': "Fit each design's reviewed records and evaluate those same records. This is training fit only.", 'train_all': 'Experimental fit on eligible automatic scan-projected weak labels. Predictions are training-fit diagnostics, not independently reviewed accuracy.', 'diagnostic': 'Untrained actual-input forward passes. No accuracy is calculated.'}, 'data_selection': 'complete CAT + EXCEL + CSV + PLY matches; known duplicate sample groups excluded', 'targets': 'User-selected scan/CAD pairs with recorded mirrored frames and CAD-supported scan regions. Node targets remain automatic weak CSV/raster projections; unannotated covered nodes outside guarded regions are assumed negative.', 'scores': 'Independently reviewed accuracy is unavailable for weak supervision. Real optimizer epoch losses and checkpoints are saved; weak-label predictions never enter reviewed score averages.', 'averaging': 'Macro means are per dataset, not per node. Unscored records never enter the average.', 'uncertainty': 'GP posterior standard deviations are available when fitted. Other models have no calibrated uncertainty claim.', 'deformation': 'Physics GNN deformation/type heads are not supervised by this node-risk contract and are not scored.', 'limitations': 'User confirmation applies to pair inclusion. CAD-node ground truth remains unreviewed. Rejected CSV rows and their nearby assumed negatives are masked; source choices, reflection, raw residuals and partial scan coverage remain recorded.', 'statuses': {'untrained_diagnostic': 126, 'completed': 280, 'requires_training_labels': 14, 'unavailable_backend': 42}, 'failures': [{'model_id': 'gaussian_process', 'protocol': 'diagnostic', 'design_id': 'AC28_DT_RR_FRT_UPR_LH_07d0fbeba5ef', 'dataset_id': 'AC28_DT_FRT_UPR_LHD_20260909_15_15__NG_a22f7d301de4', 'status': 'requires_training_labels', 'reason': 'GP requires a fitted training posterior; no random/synthetic prior score emitted'}, {'model_id': 'gaussian_process', 'protocol': 'diagnostic', 'design_id': 'AC28_DT_RR_UPR_STD_6f8b270d95b5', 'dataset_id': 'AC28_DT_RR_UPR_STD_1_20260827_18_01__NG_7194c0e36c7b', 'status': 'requires_training_labels', 'reason': 'GP requires a fitted training posterior; no random/synthetic prior score emitted'}, {'model_id': 'gaussian_process', 'protocol': 'diagnostic', 'design_id': 'AC28_DT_RR_UPR_STD_6f8b270d95b5', 'dataset_id': 'AC28_DT_RR_UPR_STD_20260827_16__NG_008adde420f0', 'status': 'requires_training_labels', 'reason': 'GP requires a fitted training posterior; no random/synthetic prior score emitted'}, {'model_id': 'gaussian_process', 'protocol': 'diagnostic', 'design_id': 'AC28_DT_RR_UPR_STD_6f8b270d95b5', 'dataset_id': 'AC28_DT_RR_UPR_STD_20260828_09_21__NG_f4c68f38e467', 'status': 'requires_training_labels', 'reason': 'GP requires a fitted training posterior; no random/synthetic prior score emitted'}, {'model_id': 'gaussian_process', 'protocol': 'diagnostic', 'design_id': 'AC28_DT_RR_UPR_STD_6f8b270d95b5', 'dataset_id': 'AC28_DT_RR_UPR_STD_2_20260827_18_01__NG_8df93616f7ea', 'status': 'requires_training_labels', 'reason': 'GP requires a fitted training posterior; no random/synthetic prior score emitted'}, {'model_id': 'gaussian_process', 'protocol': 'diagnostic', 'design_id': 'LT2_DT_FRT_AREST_IMG-261014_35afb132841b', 'dataset_id': 'LT2_DT_FRT_AREST2_20260914_15_10__NG_243895937535', 'status': 'requires_training_labels', 'reason': 'GP requires a fitted training posterior; no random/synthetic prior score emitted'}, {'model_id': 'gaussian_process', 'protocol': 'diagnostic', 'design_id': 'ME1a_DT_FRT_UPR_LHD_94719179587d', 'dataset_id': 'ME1a_DT_FRT_UPR_LHD_20260608_14_06__NG_ffc4fce5d996', 'status': 'requires_training_labels', 'reason': 'GP requires a fitted training posterior; no random/synthetic prior score emitted'}, {'model_id': 'gaussian_process', 'protocol': 'diagnostic', 'design_id': 'MX5a_PE_DT_RR_ARMREST_LRH_261014_3e74cd458a06', 'dataset_id': 'MX5a_PE_DT_RR_AREST_1_20260626_13_08__NG_fe0e1b9b8b53', 'status': 'requires_training_labels', 'reason': 'GP requires a fitted training posterior; no random/synthetic prior score emitted'}, {'model_id': 'gaussian_process', 'protocol': 'diagnostic', 'design_id': 'MX5a_PE_DT_RR_ARMREST_LRH_261014_3e74cd458a06', 'dataset_id': 'MX5a_PE_DT_RR_AREST_2_20260626_13_08__NG_41ec5d7a218e', 'status': 'requires_training_labels', 'reason': 'GP requires a fitted training posterior; no random/synthetic prior score emitted'}, {'model_id': 'gaussian_process', 'protocol': 'diagnostic', 'design_id': 'NX5___RR_DT_UPR_2_CUR_TPO___261014_d11283a03a71', 'dataset_id': 'NX5_DT_RR_UPR-2_CUR_1_20260916_10_40__NG_1f98f526a60c', 'status': 'requires_training_labels', 'reason': 'GP requires a fitted training posterior; no random/synthetic prior score emitted'}, {'model_id': 'gaussian_process', 'protocol': 'diagnostic', 'design_id': 'NX5___RR_DT_UPR_2_CUR_TPO___261014_d11283a03a71', 'dataset_id': 'NX5_DT_RR_UPR-2_CUR_1_20260916_10_53__NG_b3a8f50d89ae', 'status': 'requires_training_labels', 'reason': 'GP requires a fitted training posterior; no random/synthetic prior score emitted'}, {'model_id': 'gaussian_process', 'protocol': 'diagnostic', 'design_id': 'NX5___RR_DT_UPR_2_CUR_TPO___261014_d11283a03a71', 'dataset_id': 'NX5_DT_RR_UPR-2_CUR_1_20260916_11_40__NG_1b598f48d4e1', 'status': 'requires_training_labels', 'reason': 'GP requires a fitted training posterior; no random/synthetic prior score emitted'}, {'model_id': 'gaussian_process', 'protocol': 'diagnostic', 'design_id': 'NX5___RR_DT_UPR_2_CUR_TPO___261014_d11283a03a71', 'dataset_id': 'NX5_DT_RR_UPR-2_CUR_2_20260916_10_40__NG_4debd31ebf8a', 'status': 'requires_training_labels', 'reason': 'GP requires a fitted training posterior; no random/synthetic prior score emitted'}, {'model_id': 'gaussian_process', 'protocol': 'diagnostic', 'design_id': 'NX5___RR_DT_UPR_2_CUR_TPO___261014_d11283a03a71', 'dataset_id': 'NX5_DT_RR_UPR-2_CUR_2_20260916_10_53__NG_a9e70207f7eb', 'status': 'requires_training_labels', 'reason': 'GP requires a fitted training posterior; no random/synthetic prior score emitted'}, {'model_id': 'sparse_unet', 'protocol': 'diagnostic', 'design_id': 'AC28_DT_RR_FRT_UPR_LH_07d0fbeba5ef', 'dataset_id': 'AC28_DT_FRT_UPR_LHD_20260909_15_15__NG_a22f7d301de4', 'status': 'unavailable_backend', 'reason': 'RuntimeError: RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'diagnostic', 'design_id': 'AC28_DT_RR_UPR_STD_6f8b270d95b5', 'dataset_id': 'AC28_DT_RR_UPR_STD_1_20260827_18_01__NG_7194c0e36c7b', 'status': 'unavailable_backend', 'reason': 'RuntimeError: RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'diagnostic', 'design_id': 'AC28_DT_RR_UPR_STD_6f8b270d95b5', 'dataset_id': 'AC28_DT_RR_UPR_STD_20260827_16__NG_008adde420f0', 'status': 'unavailable_backend', 'reason': 'RuntimeError: RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'diagnostic', 'design_id': 'AC28_DT_RR_UPR_STD_6f8b270d95b5', 'dataset_id': 'AC28_DT_RR_UPR_STD_20260828_09_21__NG_f4c68f38e467', 'status': 'unavailable_backend', 'reason': 'RuntimeError: RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'diagnostic', 'design_id': 'AC28_DT_RR_UPR_STD_6f8b270d95b5', 'dataset_id': 'AC28_DT_RR_UPR_STD_2_20260827_18_01__NG_8df93616f7ea', 'status': 'unavailable_backend', 'reason': 'RuntimeError: RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'diagnostic', 'design_id': 'LT2_DT_FRT_AREST_IMG-261014_35afb132841b', 'dataset_id': 'LT2_DT_FRT_AREST2_20260914_15_10__NG_243895937535', 'status': 'unavailable_backend', 'reason': 'RuntimeError: RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'diagnostic', 'design_id': 'ME1a_DT_FRT_UPR_LHD_94719179587d', 'dataset_id': 'ME1a_DT_FRT_UPR_LHD_20260608_14_06__NG_ffc4fce5d996', 'status': 'unavailable_backend', 'reason': 'RuntimeError: RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'diagnostic', 'design_id': 'MX5a_PE_DT_RR_ARMREST_LRH_261014_3e74cd458a06', 'dataset_id': 'MX5a_PE_DT_RR_AREST_1_20260626_13_08__NG_fe0e1b9b8b53', 'status': 'unavailable_backend', 'reason': 'RuntimeError: RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'diagnostic', 'design_id': 'MX5a_PE_DT_RR_ARMREST_LRH_261014_3e74cd458a06', 'dataset_id': 'MX5a_PE_DT_RR_AREST_2_20260626_13_08__NG_41ec5d7a218e', 'status': 'unavailable_backend', 'reason': 'RuntimeError: RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'diagnostic', 'design_id': 'NX5___RR_DT_UPR_2_CUR_TPO___261014_d11283a03a71', 'dataset_id': 'NX5_DT_RR_UPR-2_CUR_1_20260916_10_40__NG_1f98f526a60c', 'status': 'unavailable_backend', 'reason': 'RuntimeError: RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'diagnostic', 'design_id': 'NX5___RR_DT_UPR_2_CUR_TPO___261014_d11283a03a71', 'dataset_id': 'NX5_DT_RR_UPR-2_CUR_1_20260916_10_53__NG_b3a8f50d89ae', 'status': 'unavailable_backend', 'reason': 'RuntimeError: RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'diagnostic', 'design_id': 'NX5___RR_DT_UPR_2_CUR_TPO___261014_d11283a03a71', 'dataset_id': 'NX5_DT_RR_UPR-2_CUR_1_20260916_11_40__NG_1b598f48d4e1', 'status': 'unavailable_backend', 'reason': 'RuntimeError: RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'diagnostic', 'design_id': 'NX5___RR_DT_UPR_2_CUR_TPO___261014_d11283a03a71', 'dataset_id': 'NX5_DT_RR_UPR-2_CUR_2_20260916_10_40__NG_4debd31ebf8a', 'status': 'unavailable_backend', 'reason': 'RuntimeError: RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'diagnostic', 'design_id': 'NX5___RR_DT_UPR_2_CUR_TPO___261014_d11283a03a71', 'dataset_id': 'NX5_DT_RR_UPR-2_CUR_2_20260916_10_53__NG_a9e70207f7eb', 'status': 'unavailable_backend', 'reason': 'RuntimeError: RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'leave_one_design_out', 'design_id': 'AC28_DT_RR_FRT_UPR_LH_07d0fbeba5ef', 'dataset_id': 'AC28_DT_FRT_UPR_LHD_20260909_15_15__NG_a22f7d301de4', 'status': 'unavailable_backend', 'reason': 'RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'leave_one_design_out', 'design_id': 'AC28_DT_RR_UPR_STD_6f8b270d95b5', 'dataset_id': 'AC28_DT_RR_UPR_STD_1_20260827_18_01__NG_7194c0e36c7b', 'status': 'unavailable_backend', 'reason': 'RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'leave_one_design_out', 'design_id': 'AC28_DT_RR_UPR_STD_6f8b270d95b5', 'dataset_id': 'AC28_DT_RR_UPR_STD_20260827_16__NG_008adde420f0', 'status': 'unavailable_backend', 'reason': 'RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'leave_one_design_out', 'design_id': 'AC28_DT_RR_UPR_STD_6f8b270d95b5', 'dataset_id': 'AC28_DT_RR_UPR_STD_20260828_09_21__NG_f4c68f38e467', 'status': 'unavailable_backend', 'reason': 'RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'leave_one_design_out', 'design_id': 'AC28_DT_RR_UPR_STD_6f8b270d95b5', 'dataset_id': 'AC28_DT_RR_UPR_STD_2_20260827_18_01__NG_8df93616f7ea', 'status': 'unavailable_backend', 'reason': 'RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'leave_one_design_out', 'design_id': 'LT2_DT_FRT_AREST_IMG-261014_35afb132841b', 'dataset_id': 'LT2_DT_FRT_AREST2_20260914_15_10__NG_243895937535', 'status': 'unavailable_backend', 'reason': 'RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'leave_one_design_out', 'design_id': 'ME1a_DT_FRT_UPR_LHD_94719179587d', 'dataset_id': 'ME1a_DT_FRT_UPR_LHD_20260608_14_06__NG_ffc4fce5d996', 'status': 'unavailable_backend', 'reason': 'RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'leave_one_design_out', 'design_id': 'MX5a_PE_DT_RR_ARMREST_LRH_261014_3e74cd458a06', 'dataset_id': 'MX5a_PE_DT_RR_AREST_1_20260626_13_08__NG_fe0e1b9b8b53', 'status': 'unavailable_backend', 'reason': 'RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'leave_one_design_out', 'design_id': 'MX5a_PE_DT_RR_ARMREST_LRH_261014_3e74cd458a06', 'dataset_id': 'MX5a_PE_DT_RR_AREST_2_20260626_13_08__NG_41ec5d7a218e', 'status': 'unavailable_backend', 'reason': 'RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'leave_one_design_out', 'design_id': 'NX5___RR_DT_UPR_2_CUR_TPO___261014_d11283a03a71', 'dataset_id': 'NX5_DT_RR_UPR-2_CUR_1_20260916_10_40__NG_1f98f526a60c', 'status': 'unavailable_backend', 'reason': 'RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'leave_one_design_out', 'design_id': 'NX5___RR_DT_UPR_2_CUR_TPO___261014_d11283a03a71', 'dataset_id': 'NX5_DT_RR_UPR-2_CUR_1_20260916_10_53__NG_b3a8f50d89ae', 'status': 'unavailable_backend', 'reason': 'RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'leave_one_design_out', 'design_id': 'NX5___RR_DT_UPR_2_CUR_TPO___261014_d11283a03a71', 'dataset_id': 'NX5_DT_RR_UPR-2_CUR_1_20260916_11_40__NG_1b598f48d4e1', 'status': 'unavailable_backend', 'reason': 'RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'leave_one_design_out', 'design_id': 'NX5___RR_DT_UPR_2_CUR_TPO___261014_d11283a03a71', 'dataset_id': 'NX5_DT_RR_UPR-2_CUR_2_20260916_10_40__NG_4debd31ebf8a', 'status': 'unavailable_backend', 'reason': 'RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'leave_one_design_out', 'design_id': 'NX5___RR_DT_UPR_2_CUR_TPO___261014_d11283a03a71', 'dataset_id': 'NX5_DT_RR_UPR-2_CUR_2_20260916_10_53__NG_a9e70207f7eb', 'status': 'unavailable_backend', 'reason': 'RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'train_all', 'design_id': 'AC28_DT_RR_FRT_UPR_LH_07d0fbeba5ef', 'dataset_id': 'AC28_DT_FRT_UPR_LHD_20260909_15_15__NG_a22f7d301de4', 'status': 'unavailable_backend', 'reason': 'RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'train_all', 'design_id': 'AC28_DT_RR_UPR_STD_6f8b270d95b5', 'dataset_id': 'AC28_DT_RR_UPR_STD_1_20260827_18_01__NG_7194c0e36c7b', 'status': 'unavailable_backend', 'reason': 'RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; dense tensors are not a sparse substitute.'}, {'model_id': 'sparse_unet', 'protocol': 'train_all', 'design_id': 'AC28_DT_RR_UPR_STD_6f8b270d95b5', 'dataset_id': 'AC28_DT_RR_UPR_STD_20260827_16__NG_008adde420f0', 'status': 'unavailable_backend', 'reason': 'RuntimeError: Sparse U-Net unavailable: install optional MinkowskiEngine; 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