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      ],
      "metrics": [
        {
          "AP": 0.5374004015308363,
          "IoU_at_0.5": 0.06521739130434782,
          "Dice_at_0.5": 0.12244897959183673,
          "target_nodes": 6,
          "predicted_nodes": 92
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        {
          "AP": 0.09233445740989267,
          "IoU_at_0.5": 0.02826086956521739,
          "Dice_at_0.5": 0.05496828752642706,
          "target_nodes": 17,
          "predicted_nodes": 456
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      ]
    }
  ],
  "inputs": {
    "surface_graph": "data_processed/graphs/graph_6000.npz",
    "requested_node_budget": 6000,
    "actual_node_count": 5925,
    "triangle_count": 11999,
    "training_inference_viewer_outputs": "same prepared graph_6000 with 5,925 actual nodes",
    "node_density_is_risk_feature": false,
    "normal_baseline": "same GNN/seed/epochs/loss/process/threshold; excludes curvature, analytic curvature, boundary/ridge and face dihedral",
    "dihedral_face_definition": "acos(clamp(dot(two adjacent face normals), -1,1)); undefined on boundary/nonmanifold",
    "changed_cad": "A new CAD can execute with variable node count/topology, but this experiment fixes the ~6k preparation rule: independently simplify each new CAD with the same rule; node indices never correspond across designs; output is direct per-new-CAD-node. Generalization is unmeasured with one CAD/two runs. Use multi-design training, CAD-family held-out splits and OOD uncertainty before interpreting cross-design output.",
    "features": {
      "normal_baseline": {
        "node": [
          "pos_norm_x",
          "pos_norm_y",
          "pos_norm_z",
          "normal_x",
          "normal_y",
          "normal_z",
          "vertex_area_mm2",
          "mean_incident_angle_rad",
          "topological_degree"
        ],
        "edge": [
          "length_mm",
          "direction_x",
          "direction_y",
          "direction_z",
          "normal_dot"
        ]
      },
      "dihedral_aware": {
        "node": [
          "pos_norm_x",
          "pos_norm_y",
          "pos_norm_z",
          "normal_x",
          "normal_y",
          "normal_z",
          "vertex_area_mm2",
          "mean_incident_angle_rad",
          "mean_curvature_abs_1_per_mm",
          "gaussian_curvature_abs_1_per_mm2",
          "boundary_node",
          "feature_node",
          "topological_degree",
          "analytic_k1_abs_1_per_mm",
          "analytic_k2_abs_1_per_mm",
          "analytic_gaussian_signed_1_per_mm2",
          "cad_k1_signed_1_per_mm",
          "cad_k2_signed_1_per_mm",
          "cad_mean_H_signed_1_per_mm",
          "cad_gaussian_K_1_per_mm2",
          "cad_curvedness_1_per_mm",
          "cad_shape_index"
        ],
        "edge": [
          "length_mm",
          "direction_x",
          "direction_y",
          "direction_z",
          "normal_dot",
          "dihedral_rad",
          "boundary_edge",
          "feature_edge"
        ]
      }
    }
  },
  "changed_cad": "A new CAD can execute with variable node count/topology, but this experiment fixes the ~6k preparation rule: independently simplify each new CAD with the same rule; node indices never correspond across designs; output is direct per-new-CAD-node. Generalization is unmeasured with one CAD/two runs. Use multi-design training, CAD-family held-out splits and OOD uncertainty before interpreting cross-design output.",
  "conceptual_next_model": {
    "status": "conceptual_next_model_not_trained",
    "branches": "CAD graph geometry encoder (curvature/face-dihedral/ridge/boundary) + XLS thermal/process encoder; local thermal projection only when heater footprints exist",
    "node_heads": "segmentation/risk/deformation/thinning",
    "region_heads": "defect type and physical area mm²",
    "identifiability": "thermal risk and geometry risk cannot be separated from one fused label without branch-specific targets, controlled variation or concept supervision",
    "current_data": "one CAD, two NG runs, only 찍힘, no observed area; weak dilation is not physical area",
    "physics_needed": "local temperature, thickness/material/FLC/contact and measured strain/stress or simulation targets are required for causal sharp-bump→strain→tear claims"
  },
  "limitations": [
    "diagnostic weak-label fit; not a physical tear/defect predictor"
  ]
}