Revision 3: exact-zero stop in section 4; Table 12 with the post hoc Lagouanelle variant (branch m>=2: corpus 4 5568, six corpora 18372, multiple/fractional 6540, APS 2960; A' 178/34/28), the controls' missing exit in its caption; the reading of Table 12 restated in 7.1, 6.6 and the conclusion - the analogy order transfers to the classical frame and works better there than in A's split (2809 vs 4042 on multiple roots), and A's layer as a whole (detector with exit) earns its place (+1233 vs -3934). Server: verify 548 OK / 0 BAD, regression x2 1239 passed, PDF 32 pages, 0 errors, 0 overfull.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

sweep_estimated_posthoc.py

@@ -0,0 +1,84 @@
+"""POSTHOC_lag_branch_2026-09-22: Chandrupatla on sign(f)|f|^(1/m_hat) with Lagouanelle's estimate
+restricted to the branch m >= 2 (K3-L2), post hoc, with the harness of sweep_fourth.py.  The
+registered K3 run (sweep_estimated.py / .json) is not touched.
+
+    python -u sweep_estimated_posthoc.py            run -> sweep_estimated_posthoc.json, report
+    python -u sweep_estimated_posthoc.py --report
+"""
+from __future__ import annotations
+
+import functools
+import json
+import sys
+from multiprocessing import Pool
+
+import sweep_fourth
+import sweep_full
+from simroot.transformed import chandrupatla_transformed
+from sweep_controls import nonsimple
+from sweep_oos import sign_p
+
+sweep_full.EXTRA_BASELINES["k3_lag2"] = functools.partial(chandrupatla_transformed, estimator="lag2")
+sweep_fourth.CONFIGS["k3_lag2"] = ("base", "k3_lag2")
+SETS = ("APS", "CHA", "NEW", "RJL", "APP", "D")
+
+
+def job(which):
+    return sweep_fourth.evaluate(("k3_lag2", which))[1]
+
+
+def cost(v):
+    return v[0] if v[1] else 200
+
+
+def tot(r, keep=None):
+    return sum(cost(v) for p, v in r.items() if keep is None or keep(p))
+
+
+def held_on_simple_roots():
+    """How many APS runs end holding m_hat != 1 (fresh)."""
+    n = 0
+    for s, pid, f, a, b, _r in sweep_full.load_problems():
+        if s != "APS":
+            continue
+        st = {}
+        chandrupatla_transformed(f, a, b, 1e-12, 200, estimator="lag2", stats=st)
+        n += st.get("m_hat", 1.0) != 1.0
+    return n
+
+
+def report(R):
+    seen = json.load(open("sweep_fourth_seen.json", encoding="utf8"))
+    four = json.load(open("sweep_fourth_fourth.json", encoding="utf8"))
+    ap = dict(seen["Aprime"])
+    ap.update(four["Aprime"])
+    K1 = json.load(open("sweep_controls.json", encoding="utf8"))["K1"]
+    grp = sum(tot(R[s], lambda p, _m=K1[s]["mstar"]: nonsimple(_m[p])) for s in ("CHA", "NEW", "D"))
+    ps = list(ap["D"])
+    w = sum(cost(ap["D"][p]) < cost(R["D"][p]) for p in ps)
+    l = sum(cost(ap["D"][p]) > cost(R["D"][p]) for p in ps)
+    print(f"K3-L2 (post hoc): corpus 4 {tot(R['D'])}  six corpora {sum(tot(R[s]) for s in SETS)}  "
+          f"multiple/fractional {grp}  APS {tot(R['APS'])}")
+    print(f"  A' on corpus 4 against it: {w}/{len(ps) - w - l}/{l}  p={sign_p(w, l):.2g}")
+    print(f"  per corpus: " + " ".join(f"{s} {tot(R[s])}" for s in SETS))
+    print(f"  violations {sum(v[2] for s in SETS for v in R[s].values())}")
+    print(f"  APS runs ending with m_hat != 1: {held_on_simple_roots()} of 154")
+
+
+def main():
+    if "--report" not in sys.argv:
+        with Pool(2) as pool:
+            parts = pool.map(job, ("seen", "fourth"))
+        R = {}
+        for p in parts:
+            R.update(p)
+        with open("sweep_estimated_posthoc.json", "w", encoding="utf8") as fh:
+            json.dump(R, fh)
+    with open("sweep_estimated_posthoc.json", encoding="utf8") as fh:
+        R = json.load(fh)
+    report(R)
+    print("posthoc done")
+
+
+if __name__ == "__main__":
+    main()