Remove old README_universal_v2.md (renamed to main_benchmark)

README_universal_v2.md

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-# Universal_v2 benchmark — scoring scripts + reference structures
-
-Two-state / multi-conformer benchmark of 60 cases across four patterns
-(FS fold-switch, AL allosteric, ID disorder-to-order, OL oligomer), 6 MSA-subsampling
-methods each. This package ships the **scoring code** and the **per-case reference
-structures + region definitions** so predictions can be scored and the benchmark
-tables regenerated on CPU. The AlphaFold2 prediction PDBs (~16 GB) are **not**
-distributed here — bring your own, or score the reference set.
-
-## Contents
-
-- `eval/universal_v2_evaluate.py` — per-prediction scorer. For each state (a, b):
-  Cα RMSD on the common core, optional TM-score, and `hit_primary` (§9.1 binding
-  3-condition: RMSD ≤ 3 Å on common core AND mean pLDDT ≥ 70 AND switch-region
-  pLDDT ≥ 70). Pure CPU: `numpy`, `biopython`, `pyyaml`. TMalign optional (extra
-  columns only).
-- `eval/aggregate_universal_v2.py` — aggregate per-(case, method) `evals.tsv` into
-  `main_table.csv` (per case×method hit counts/rates) and `pattern_summary.csv`
-  (per pattern×method means).
-- `bench/universal_v2/structures/<case_id>/{state_a,state_b}.pdb` — 60 cases, 120 references.
-- `bench/universal_v2/annotations/<case_id>/state_region_FINAL.tsv` — common-core and
-  switch-region residue indices (evaluator input only; oracle annotation, not a feature).
-- `bench/universal_v2/cases.yaml` — case metadata.
-
-## Usage
-
-```bash
-pip install numpy biopython pyyaml   # TMalign optional
-
-# Score one case×method directory of prediction PDBs:
-python eval/universal_v2_evaluate.py \
-    --case SFB_FS_A1AT_1QLPA_1OPHA \
-    --root /path/to/predictions/<case>/<method>/refine_per_state \
-    --out evals.tsv
-
-# Aggregate a full results tree (SF_UV2_RESULTS/<case>/<method>/refine_per_state/evals.tsv):
-SF_UV2_RESULTS=/path/to/results python eval/aggregate_universal_v2.py
-```
-
-`SF_UV2_DATA` defaults to the bundled `bench/universal_v2` (structures + annotations +
-cases.yaml); override to point elsewhere. `SF_UV2_RESULTS` supplies the predictions tree.
-
-## Verification
-
-The scorer is deterministic. Re-scoring the internal prediction set reproduces the
-published hit flags exactly (2594/2594 predictions across a 12-case stratified sample;
-`main_table` → `pattern_summary` aggregation reproduces 24/24 rows; `main_table` hit
-counts reproduce from `evals.tsv` 360/360). Headline: mosaic-SF beats AF-Cluster by
-~5–18 pp across patterns but is statistically indistinguishable from depth-matched
-random subsampling.