{
  "_notes": [
    "Geometry vector injection via UNet (no GT, no seg-CNN tower).",
    "img tower runs UNet per-fold to predict disc/cup masks, computes 5 CDR",
    "features per eye, publishes to EPC; cd tower consumes them.",
    "Same shape as ensemble_fused.json — just adds the UNet-derived geometry hook."
  ],
  "run_name": "v4/ensemble_fused_geom_unet",
  "num_classes": 2,
  "label_filter": [0, 1],
  "split_identity_level": 1,
  "eval_stage": "hb",
  "save_predictions": true,
  "seed": 1234,
  "folds": 5,
  "fold_seed": 100,
  "output_root": "v4/results",
  "out_dir_tags": ["binary"],

  "data": {
    "module": "v4.classes.profiles.v4papila",
    "args": {
      "image_dir": "Papila/FundusImages",
      "clinical_dir": "Papila/ClinicalData",
      "label_col": "Diagnosis",
      "iop_corr_method": "ratio",
      "iop_drop_raw": true,
      "exclude_cols": ["Axial_Length"],
      "in_memory_cache": true
    }
  },

  "towers": [
    {
      "name": "img",
      "module": "v4.classes.towers.image_tower",
      "class": "ImageEncoder",
      "data_source": "image",
      "epc_supplies": ["geometry_vectors"],
      "args": {
        "backbone":            "refugelike",
        "freeze_ratio":        0.0,
        "augment":             true,
        "geometry_source":     "unet",
        "weights_path":        "models/v2/refuge/segmentation/per_image/best.pt",
        "contour_dir":         "Papila/ExpertsSegmentations/Contours",
        "unet_size":           512,
        "normalize":           "per_image",
        "threshold":           0.5,
        "finetune_epochs":     10,
        "finetune_lr":         1e-5,
        "finetune_batch_size": 4
      }
    },
    {
      "name": "cd",
      "module": "v4.classes.towers.clinical_tower",
      "class": "ClinicalEncoder",
      "data_source": "matrix",
      "epc_requests": ["geometry_vectors"],
      "args": {
        "hidden_dim": 128,
        "geom_dim":   5
      }
    }
  ],

  "stages": [
    {
      "name": "cd_warm",
      "type": "warm",
      "tower": "cd",
      "head_name": "cd_aux",
      "level": "eye",
      "epochs": 40
    },
    {
      "name": "img_aux",
      "type": "head",
      "input": "img",
      "train_with": "nt",
      "bcd": true
    },
    {
      "name": "cd_aux",
      "type": "head",
      "input": "cd",
      "train_with": "nt",
      "bcd": true
    },
    {
      "name": "nt",
      "type": "fusion",
      "module": "v4.classes.bridges.fusion_bridge",
      "class": "FusionBridge",
      "inputs": ["img", "cd"],
      "level": "eye",
      "epochs": 36,
      "train_towers": true,
      "warmup": {
        "tower_epochs": 3,
        "fused_epochs": 3
      },
      "args": {
        "fusion_dim": 256
      }
    },
    {
      "name": "nt_head",
      "type": "head",
      "input": "nt",
      "train_with": "nt"
    },
    {
      "name": "hb",
      "type": "fusion",
      "module": "v4.classes.bridges.hyperbridge",
      "class": "HyperBridge",
      "inputs": { "a": "nt", "b": "nt" },
      "level": "patient",
      "epochs": 10,
      "args": {
        "hidden_dim": 256,
        "mode": "embedding_mlp"
      }
    },
    {
      "name": "hb_head",
      "type": "head",
      "input": "hb",
      "train_with": "hb",
      "args": { "dropout": 0.3 }
    }
  ],

  "training": {
    "lr": 1e-4,
    "batch_size": 8,
    "bcd_prob": 0.5,
    "tune_binary_threshold": true
  }
}