| { | |
| "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" | |
| } |