{
  "model_type": "dcpg_encoder",
  "architecture": "GAT",
  "node_feat_dim": 19,
  "hidden_dim": 32,
  "embed_dim": 16,
  "num_layers": 2,
  "pooling": "attention",
  "attention": "single_head",
  "edge_weight_formula": "0.30*f_temporal + 0.30*f_semantic + 0.25*f_modality + 0.15*f_trust",
  "input_sources": [
    "DCPGAdapter.graph_summary",
    "CRDTGraph.summary"
  ],
  "output": {
    "patient_embedding": 16,
    "node_embeddings": "per_node",
    "risk_score": "scalar_sigmoid"
  },
  "dependencies": [],
  "framework": "pure_python"
}