Add new scripts and configurations for model comparison and analysis

- Introduced `poster_model_comparison.py` for generating model comparison figures.
- Added `plot_poster_roc_comparison.py` for creating ROC comparison figures for PAPILA binary classification.
- Created new JSON configuration files for clinical solo models with and without geometry injection.
- Implemented batch dispatch updates in `batch_dispatch.py` to utilize run names from configurations.
- Added analysis scripts: `compare_grid.py`, `inspect_embeddings.py`, and `summarize_run.py` for evaluating model performance and feature embeddings.
- Created experiment configurations for various training scenarios, including warm sweeps and promoting successful runs.
- Added binary ROC comparison and model comparison figures to the results directory.

v4/scripts/analysis/compare_grid.py

@@ -0,0 +1,112 @@
+"""compare_grid — print a ranked comparison table for a folder of v4 runs.
+
+A "grid" folder is one whose immediate children are individual run folders, e.g.
+``v4/results/experiments/tri_v1/grid/`` containing ``bcd35_cw0_nt15/``,
+``bcd35_cw0_nt25/``, etc.  Each child must itself look like a run folder
+(``repNN/.../summary.json``).
+
+Usage:
+    python -m v4.scripts.analysis.compare_grid <grid_folder>
+        [--sort {test,val,name,reps}] [--reverse] [--csv]
+
+Examples:
+    python -m v4.scripts.analysis.compare_grid \
+        v4/results/experiments/tri_v1/grid
+    python -m v4.scripts.analysis.compare_grid \
+        v4/results/experiments/tri_v1 --sort test
+"""
+from __future__ import annotations
+
+import argparse
+import csv
+import sys
+from pathlib import Path
+
+from v4.scripts.analysis.summarize_run import summarise
+
+
+def collect(grid_dir: Path) -> list[dict]:
+    rows: list[dict] = []
+    for child in sorted(grid_dir.iterdir()):
+        if not child.is_dir():
+            continue
+        s = summarise(child)
+        if s["n_reps"] == 0:
+            continue
+        rows.append({
+            "name":      child.name,
+            "n":         s["n_reps"],
+            "val_mean":  s["val_mean"],
+            "val_std":   s["val_std"],
+            "test_mean": s["test_mean"],
+            "test_std":  s["test_std"],
+        })
+    return rows
+
+
+def render_table(rows: list[dict]) -> str:
+    if not rows:
+        return "(no runs found)"
+    name_w = max(len("name"), max(len(r["name"]) for r in rows))
+    header = f"{'name':<{name_w}s}  {'reps':>4s}  {'val AUC':>17s}  {'test AUC':>17s}"
+    sep    = "-" * len(header)
+    lines  = [header, sep]
+    for r in rows:
+        lines.append(
+            f"{r['name']:<{name_w}s}  {r['n']:>4d}  "
+            f"{r['val_mean']:.4f} ± {r['val_std']:.4f}  "
+            f"{r['test_mean']:.4f} ± {r['test_std']:.4f}"
+        )
+    return "\n".join(lines)
+
+
+def render_csv(rows: list[dict]) -> str:
+    buf = sys.stdout
+    w   = csv.writer(buf)
+    w.writerow(["name", "reps", "val_mean", "val_std", "test_mean", "test_std"])
+    for r in rows:
+        w.writerow([r["name"], r["n"],
+                    f"{r['val_mean']:.6f}", f"{r['val_std']:.6f}",
+                    f"{r['test_mean']:.6f}", f"{r['test_std']:.6f}"])
+    return ""
+
+
+_SORT_KEYS = {
+    "test":  lambda r: r["test_mean"],
+    "val":   lambda r: r["val_mean"],
+    "name":  lambda r: r["name"],
+    "reps":  lambda r: r["n"],
+}
+
+
+def main():
+    ap = argparse.ArgumentParser(description=__doc__,
+                                 formatter_class=argparse.RawDescriptionHelpFormatter)
+    ap.add_argument("grid_dir", type=Path,
+                    help="Folder whose immediate children are run folders")
+    ap.add_argument("--sort", choices=list(_SORT_KEYS),
+                    default="test", help="Sort by which column (default: test)")
+    ap.add_argument("--reverse", action="store_true",
+                    help="Reverse the default ordering")
+    ap.add_argument("--csv", action="store_true",
+                    help="Emit CSV to stdout instead of a formatted table")
+    args = ap.parse_args()
+
+    if not args.grid_dir.is_dir():
+        raise SystemExit(f"Not a directory: {args.grid_dir}")
+
+    rows = collect(args.grid_dir)
+    descending = args.sort in {"test", "val", "reps"}
+    if args.reverse:
+        descending = not descending
+    rows.sort(key=_SORT_KEYS[args.sort], reverse=descending)
+
+    if args.csv:
+        render_csv(rows)
+    else:
+        print(f"Grid: {args.grid_dir}  ({len(rows)} runs, sorted by {args.sort})\n")
+        print(render_table(rows))
+
+
+if __name__ == "__main__":
+    main()