{
  "_notes": [
    "Standalone geometry tower: GeometrySegEncoder over UNet-derived seg maps,",
    "MonoBridge passthrough, classification head.  Same architecture as the",
    "seg_cnn_unet_ft_mono test run, used as a 10-rep baseline for comparison",
    "against tritower configurations."
  ],
  "run_name": "v4/geometry_solo",
  "num_classes": 2,
  "label_filter": [0, 1],
  "split_identity_level": 1,
  "eval_stage": "geom_fuse",
  "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": false
    }
  },

  "towers": [
    {
      "name": "geom",
      "module": "v4.classes.towers.geometry_tower",
      "class": "GeometrySegEncoder",
      "data_source": "image",
      "args": {
        "backbone":            "resnet18",
        "channels":            3,
        "target_size":         224,
        "augment":             true,
        "freeze_ratio":        0.0,
        "seg_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,
        "crop_to_disc":        true,
        "finetune_epochs":     10,
        "finetune_lr":         1e-5,
        "finetune_batch_size": 4
      }
    }
  ],

  "stages": [
    {
      "name": "geom_fuse",
      "type": "fusion",
      "module": "v4.classes.bridges.mono_bridge",
      "class": "MonoBridge",
      "inputs": ["geom"],
      "level": "eye",
      "epochs": 60,
      "train_towers": true,
      "args": { "use_ln": false }
    },
    {
      "name": "geom_head",
      "type": "head",
      "input": "geom_fuse",
      "train_with": "geom_fuse",
      "args": { "dropout": 0.3 }
    }
  ],

  "training": {
    "lr": 1e-4,
    "batch_size": 16,
    "tune_binary_threshold": true
  }
}