Add new experiments and analysis scripts for dropzero features

- Introduced `fused_importance_with_axial.py` to evaluate the importance of Axial_Length in the fused-head model.
- Created JSON configurations for various experiments excluding zero-importance clinical features:
  - `cd_solo_bilateral_dropzero.json`: Bilateral clinical-only evaluation.
  - `cd_solo_single_dropzero.json`: Single-eye clinical-only evaluation.
  - `ensemble_refugelike_ckpt_dropzero.json`: Ensemble model with dropped zero-importance features.
  - `ensemble_single_refugelike_dropzero.json`: Single-eye ensemble model with dropped features.

v4/scripts/experiments/explainability/ensemble_refugelike_ckpt_dropzero.json

@@ -0,0 +1,21 @@
+[
+  {
+    "_note": "Same 10-rep checkpointed R50 ensemble as ensemble_refugelike_ckpt, but with the four clinical features that scored ~0 fused-head permutation importance dropped from the input matrix (astigmatism, dioptre_1, dioptre_2, Phakic/Pseudophakic). eyeID is not listed here because the PAPILA profile also uses it as the OD/OS index level and dropping it via exclude_cols crashes downstream indexing; since eyeID's L2 importance is exactly 0.0 in the current CSV (fused head always sees both eyes, so eyeID carries zero information at that layer), leaving it in has no measurable effect on AUC. Same seed / fold_seed defaults as the main ckpt run so results are rep-paired for direct comparison.",
+    "run_name": "experiments/explainability/ensemble_refugelike_ckpt_dropzero",
+    "reps": 10,
+    "overrides": {
+      "save_checkpoints": true,
+      "data": {
+        "args": {
+          "exclude_cols": [
+            "Axial_Length",
+            "astigmatism",
+            "dioptre_1",
+            "dioptre_2",
+            "Phakic/Pseudophakic"
+          ]
+        }
+      }
+    }
+  }
+]