cv: SCORE line shows SE + 95% CI (scenario-scatter caveat; paired deltas remain the decision statistic)

batteryswap_example/cv.py

@@ -289,8 +289,14 @@ def report(df):
         print(f"{name:16s} {len(d):3d} {d['total_cost'].mean():8.1f} "
               f"{d['late_swap'].mean():7.1f} {d['early_swap'].mean():6.1f} "
               f"{d['n_swaps'].mean():5.1f}")
-    print(f"\nSCORE (all-building out-of-fold cost, mean over the 48 "
-          f"scenarios): {g['total_cost'].mean():.1f}")
+    tc = g['total_cost']
+    se = tc.std(ddof=1) / np.sqrt(len(tc))
+    print(f"\nSCORE (all-building out-of-fold cost, mean over the {len(tc)} "
+          f"scenarios): {tc.mean():.1f} ± {se:.1f} (SE; 95% CI "
+          f"{tc.mean() - 1.96 * se:.1f}..{tc.mean() + 1.96 * se:.1f})")
+    print("      NOTE: this SE is scenario-difficulty scatter, shared by "
+          "every candidate.\n      For comparisons use the PAIRED deltas "
+          "(`cv report`), whose SE is far smaller.")
 
 
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