- 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.
- Introduced `bridge_attention_ceiling_check.py` for variance decomposition analysis on bridge attention configurations.
- Added `bridge_attention_readout.py` to perform per-tower gate and contribution readouts, including AUC sanity checks.
- Created multiple JSON configuration files for backbone replication experiments, including anonymous CV variants and basic backbones.
- Implemented sensitivity experiments to evaluate the impact of axial length inclusion and EfficientNetV2-M performance at higher resolutions.
- Added a memory probe script to assess GPU memory usage during training with EfficientNetV2-M.
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