Add new regression and ensemble experiment configurations for V2-M and OrthoBridge

- Introduced multiple regression experiment configurations targeting vf_md, including:
  - cd_solo_reg_set.json: CD tower only regression setup.
  - img_solo_reg_set.json: Image tower only regression setup.
  - reg_head_epoch_sweep.json: Baseline regression sweeps at different epochs (50, 75, 100).
  - reg_head_set.json: Various regression setups including baseline and OrthoBridge configurations.
  - single_eye_reg.json: Single-eye regression setup for worst-eye aggregation analysis.

- Added ensemble configurations for OrthoBridge with different inner bridges:
  - ortho_alts_ensemble.json: Ensemble tests with ConcatBridge, PairwiseAdditiveBridge, and GatedAdditiveBridge.
  - ortho_alts_tritower.json: Tritower tests with the same inner bridges.

- Created V2-M specific configurations:
  - baseline_reg_nt50.json: Regression baseline with V2-M backbone.
  - geom_vec_gt.json and geom_vec_unet.json: Geometry vector injection experiments with V2-M.
  - single_l1_bridges.json: Single-eye ensemble experiments with various bridge types.
  - tritower_geom_gt.json: Tritower setup with GT contour-rasterized masks.

- Promoted existing experiments to higher repetitions for robustness.

v4/scripts/experiments/freeze_sweep/refugelike_freeze_sweep.json

@@ -0,0 +1,28 @@
+[
+  {
+    "_note": "refugelike (resnet50 + REFUGE fundus pretraining), freeze stem only (1/5 blocks). Tests whether even minimal anchoring helps stability.",
+    "run_name": "experiments/freeze_sweep/refugelike_freeze20",
+    "reps": 3,
+    "tower_overrides": {
+      "img": { "args": { "backbone": "refugelike", "freeze_ratio": 0.2 } }
+    }
+  },
+
+  {
+    "_note": "Freeze stem + layer1 (2/5 blocks). Keeps low-level conv filters fixed, lets layers 2-4 + fc adapt. Bumped to 10 reps to confirm the 0.9105 result vs the 10-rep baseline_ensemble at 0.8958.",
+    "run_name": "experiments/freeze_sweep/refugelike_freeze40",
+    "reps": 10,
+    "tower_overrides": {
+      "img": { "args": { "backbone": "refugelike", "freeze_ratio": 0.4 } }
+    }
+  },
+
+  {
+    "_note": "Freeze stem + layer1 + layer2 (3/5 blocks). Only the deep semantic layers adapt — most aggressive practical setting before model loses capacity.",
+    "run_name": "experiments/freeze_sweep/refugelike_freeze60",
+    "reps": 3,
+    "tower_overrides": {
+      "img": { "args": { "backbone": "refugelike", "freeze_ratio": 0.6 } }
+    }
+  }
+]