diff --git a/experiments/e57-clean-eval/AMENDMENT.md b/experiments/e57-clean-eval/AMENDMENT.md
new file mode 100644
index 0000000..652cd86
--- /dev/null
+++ b/experiments/e57-clean-eval/AMENDMENT.md
@@ -0,0 +1,18 @@
+# E57 amendment
+
+## 2026-10-03 00:25 EDT: summarise.py read a blank cell as a number
+
+All 834 registered evaluations had finished and none had failed, before
+anything was summarised. Then `summarise.py` stopped with
+`ValueError: invalid literal for int() with base 10: ''`.
+
+The cause is the six runs of E54's two loud faults, `indices:reorder` and
+`reward:short-array`. They raised an error, logged no return, and so have a
+blank `strict` in E54's `runs.csv`. `summarise.py` converted `rule` and
+`strict` to integers without allowing for a blank.
+
+The fix is in one line: a blank cell becomes `None`. A run with `None` is
+not "silent on the curve". The protocol leaves the loud faults out of every
+count, so the fix changes no count, no rule and no prediction. Nothing else
+in `summarise.py`, `verdicts.py` or `evaluate.py` changed. No result had been
+seen when the fix was made: the crash came before any output.
diff --git a/experiments/e57-clean-eval/FINDINGS.md b/experiments/e57-clean-eval/FINDINGS.md
new file mode 100644
index 0000000..7bd33af
--- /dev/null
+++ b/experiments/e57-clean-eval/FINDINGS.md
@@ -0,0 +1,110 @@
+# E57: on a clean environment, the policies behind the faults that both curve checks miss are as good as fault-free ones; every policy the faults wrecked, the curve checks had already caught
+
+2026-10-03 · guangzhao (E54's `bridges-venv`) · protocol:
+[`PROTOCOL.md`](PROTOCOL.md), after the pilot in `results/pilot/`, before
+the registered runs · amended once, see [`AMENDMENT.md`](AMENDMENT.md): a
+parsing fix in `summarise.py`, made before any output, that changes no count
+
+---
+
+## The result
+
+Each of the 834 final policies of E54 and E56 was run on a fresh gymnasium
+environment for 50 deterministic episodes, all policies on the same seeds.
+"Harmed" means its mean return, the clean return, fell more than 3 standard
+deviations below the fault-free band (`none`, seeds 10-19).
+
+Boundary-fault runs, seeds 0-2:
+
+| env | dose | harmed | silent on the curve | of them harmed |
+| --- | --- | --- | --- | --- |
+| Pendulum | one | 1/63 | 63 | 1 |
+| | 0.001 | 2/63 | 58 | 1 |
+| | 0.01 | 1/63 | 59 | 1 |
+| | 0.1 | 6/63 | 50 | 2 |
+| | 1.0 | 24/63 | 25 | 0 |
+| HalfCheetah | one | 0/63 | 60 | 0 |
+| | 0.01 | 0/63 | 57 | 0 |
+| | 1.0 | 28/63 | 31 | 0 |
+| Hopper | one | 0/69 | 69 | 0 |
+| | 0.01 | 0/69 | 66 | 0 |
+| | 1.0 | 19/69 | 35 | 0 |
+
+"Silent on the curve" means the run passed both the gain threshold and
+seed spread.
+
+Every check and prediction holds (`results/verdicts.txt`):
+- **V1:** 834 of 834 evaluations, each of 50 episodes.
+- **V2:** the 12 weights shared by two or more runs got identical clean
+  returns, so evaluation is deterministic.
+- **P1:** the harm rule flagged none of the ten fault-free band seeds in any
+  environment.
+- **P2:** at one value, 1 of 63, 0 of 63 and 0 of 69 boundary-fault runs
+  were harmed.
+- **P3:** Pendulum's `reward:zero` at every value logged 0, the best return
+  Pendulum gives, at all three seeds. Its policies scored -1196, -1550 and
+  -1639 on the clean environment, against a band of -186 ± 26.
+
+---
+
+## What it means
+
+**Every policy the faults wrecked, the curve checks had already caught.** At
+every value, the faults harmed 24, 28 and 19 runs. None of them passed
+both curve checks. At HalfCheetah and Hopper, no run that passed both checks
+was harmed, at any dose.
+
+**The faults the curve checks miss leave policies as good as fault-free
+ones.** This is an exploratory analysis, not in the protocol (`explore.py`,
+`results/explore.txt`). For each environment and dose, the runs silent on
+the curve have a mean clean return 0.03-0.65 band s.d. *above* the band.
+None is significantly below the 13 fault-free runs (two-sided Mann-Whitney
+U). The one significant difference is upward: Pendulum at every value,
+p = 0.003. At their own seed, they beat the fault-free twin by a median of 7-9 on
+Pendulum, 63-101 on HalfCheetah and 142-368 on Hopper. That is consistent with a
+change of seed, not with harm.
+
+**The exception is five Pendulum runs.** They passed both curve checks but
+scored below every one of the 13 fault-free runs, whose worst was -238:
+- `reward:f16` at 0.1%: -744;
+- `obs:swap` at 1%: -506;
+- `obs:stale` at one value: -430;
+- `final-obs:f16` at 10%: -333;
+- `obs:stale` at 10%: -277.
+
+That is 5 of 255 silent runs on Pendulum, against 0 of 13 fault-free.
+Thirteen fault-free runs cannot tell a rare harm from a rare bad seed.
+
+**So a silent fault is silent on a clean evaluation too.** In these tasks,
+with SB3's PPO, a fault that leaves the curve looking right also leaves
+the policy looking right. What it changes is the run. The weights differ
+from the run the authors think they trained, and with log faults or reward
+faults, so do the numbers they report. Pendulum's `reward:zero` is the
+extreme case: its log read 0, the best possible, while its policy scored
+-1196 to -1639. Only a check of the boundary itself, the step ledger or the
+episode record, tells such a run from a correct one.
+
+**On trusting the trainer's log.** For each run, the logged final return
+minus the clean return is in `results/summary.txt`. The fault-free runs'
+own gap is wide: Hopper's ranges from -1667 to +806. Training returns come
+from stochastic actions and the clean return from deterministic ones. A
+gap this wide hides all but gross reward faults.
+
+---
+
+## What E57 does not show
+
+* **Any trainer but SB3's PPO, or any task but these three.** On a task
+  where small changes in the data matter more, such as sparse rewards,
+  long horizons or real robots, the same faults may harm the policy.
+* **Harm too rare for 13 fault-free runs to bound.** The five Pendulum
+  outliers above are the edge of what this design can see.
+* **Harm in a comparison between methods.** E57 compares policies with the
+  fault-free band, not one method with another.
+
+Kept here, in `results/`: `clean.csv` (`summarise.py`, one row per run, with
+its clean return, harm, curve checks and logged return), `summary.txt`,
+`verdicts.txt` (`verdicts.py`), `explore.txt` (`explore.py`), `jobs.txt`,
+`load.txt`, `registered.out` and the source hashes. Each run's
+`clean_eval.json`, with all 50 episodes, is kept on guangzhao. Evaluation
+is deterministic (V2), so `run.sh` reproduces it.
diff --git a/experiments/e57-clean-eval/PROTOCOL.md b/experiments/e57-clean-eval/PROTOCOL.md
new file mode 100644
index 0000000..33043c8
--- /dev/null
+++ b/experiments/e57-clean-eval/PROTOCOL.md
@@ -0,0 +1,118 @@
+# E57 measurement protocol (pre-registered)
+
+**Written 2026-10-03, after the pilot in `results/pilot/`, before the
+registered runs.**
+
+This file must not be edited after the first registered data point. Anything
+learned afterwards goes in `AMENDMENT.md`, dated.
+
+---
+
+## The question
+
+E54 and E56 judged each run by what the trainer saw: its own log, its
+weights, or the two sides' records. None of them asks what a faulted run
+leaves behind, the policy. Reviewers asked whether the faults matter at all.
+
+**Evaluated on a clean environment, is a policy trained through a fault
+worse than one trained without it? In particular, are the faults that both
+curve checks miss?** And does the trainer's log agree with the clean
+evaluation?
+
+---
+
+## Declared in advance: what was already known
+
+1. **The policies.** Every E54 and E56 run saved its final policy
+   (`model.zip`): 590 runs of E54 (Pendulum, HalfCheetah) and 244 of E56
+   (Hopper). Their outcomes under the gain threshold, seed spread, byte
+   identity, record and ledger are published (`runs.csv`, `ledger.csv`). No
+   policy had been evaluated outside training before the pilot.
+2. **The pilot** (`results/pilot/`), 20 episodes each, on guangzhao:
+
+   | env | `none` seed 0 | `none` seed 10 | `obs:f16` 1.0 seed 0 |
+   | --- | --- | --- | --- |
+   | Pendulum | -147.0 | -139.1 | -139.7 |
+   | HalfCheetah | 647.1 | 779.8 | 851.2 |
+   | Hopper | 3368.9 | 3651.3 | 1633.5 (mean length 482) |
+
+   Pendulum's episodes vary by about 100 (initial states); HalfCheetah's by
+   about 130; Hopper's by 10-580. An evaluation took 0.3-2.5 s.
+
+---
+
+## Design
+
+`evaluate.py RUN_DIR OUT_DIR --episodes 50`. It does the following:
+- loads the run's `model.zip` on CPU, with one torch thread;
+- makes a fresh `gymnasium.make(id)` at default settings (Pendulum-v1,
+  HalfCheetah-v5, Hopper-v5), with no bridge, client, wrapper or fault;
+- plays 50 episodes with `deterministic=True`, reset with seeds 10000-10049,
+  which are the same for every policy;
+- writes `clean_eval.json`: each episode's return and length, and their mean,
+  the **clean return**.
+
+Every run directory of E54 and E56 that holds a `model.zip` is evaluated:
+834 runs, 12 at a time on guangzhao (`run.sh`). Then `python summarise.py`
+and `python verdicts.py`.
+
+---
+
+## How each run is judged
+
+- **The fault-free band**, per environment: the clean returns of `none` at
+  seeds 10-19. The band is its mean and standard deviation.
+- **Harmed:** a run's clean return is more than 3 standard deviations below
+  the band's mean. The rule is the seed-spread check's, applied to the clean
+  return, and only on the low side. A fault-free seed among 10-19 is judged
+  against the other nine.
+- **Silent on the curve:** the run passed both the gain threshold and seed
+  spread (`rule` = 0 and `strict` = 0 in E54's or E56's `runs.csv`).
+- **The log's error:** the trainer's logged final return (`last` in
+  `runs.csv`) minus the clean return.
+
+Boundary faults are E54's 21 client faults (23 on Hopper). Log faults,
+controls (`none`, `delay-1ms`, `wire-float64`) and the two loud faults
+(`indices:reorder`, `reward:short-array`) are reported separately. The
+loud faults raised an error, so they are left out of every count.
+
+---
+
+## Checks that the runs are valid
+
+- **V1:** all 834 evaluations complete, each with 50 episodes.
+- **V2:** two runs with the same weights hash get the same clean return. The
+  controls and log faults ended on `none`'s weights, so this tests that
+  evaluation is deterministic.
+
+---
+
+## Predictions, and what falsifies each
+
+**P1 - The harm rule raises few false alarms.** It flags at most 1 of the
+ten fault-free seeds 10-19 in each environment, each judged against the
+other nine. Falsified by 2 or more in any environment.
+
+**P2 - One changed value does no measurable harm.** At dose `one`, at most
+10% of boundary-fault runs are harmed, in each environment. Falsified by
+more.
+
+**P3 - A zeroed reward leaves a policy that does not work, behind a log
+that looks perfect.** On Pendulum at dose 1.0, `reward:zero` is harmed at
+all three seeds, while its log reads 0, the best return Pendulum can give.
+Falsified by any seed not harmed.
+
+> Grounds: P1, E54's and E56's seed-spread false alarms (0, 1, 0 of ten). P2,
+> one changed value moved the logged return about as much as a change of
+> seed (E54, E56). P3, with every reward zero PPO's advantages are zero
+> after normalisation, and nothing is learned.
+
+**Reported, not predicted:**
+- **The main count.** Among boundary-fault runs, at each dose:
+  - how many are harmed;
+  - how many are harmed while silent on the curve.
+- **The faults behind it.** Every fault and dose that was silent on the curve
+  at all three seeds and harmed at two or more.
+- **The log's error.** For each kind, against the fault-free runs' range.
+- **The pilot's lead.** Whether Hopper's `obs:f16` at 1.0 is harmed at seeds 1
+  and 2. The pilot saw it at seed 0 only.
diff --git a/experiments/e57-clean-eval/evaluate.py b/experiments/e57-clean-eval/evaluate.py
new file mode 100644
index 0000000..6d5a9d9
--- /dev/null
+++ b/experiments/e57-clean-eval/evaluate.py
@@ -0,0 +1,64 @@
+"""E57: evaluate one run's final policy on a clean environment.
+
+    python evaluate.py RUN_DIR OUT_DIR [--episodes N]
+
+RUN_DIR is an E54 or E56 run directory (model.zip, result.json). The policy
+acts deterministically in a fresh gymnasium environment of the same id, at
+its default settings, for N episodes reset with seeds 10000, 10001, ... No
+bridge, no env client, no fault. Writes OUT_DIR/clean_eval.json.
+"""
+
+import argparse
+import json
+import pathlib
+import time
+
+import gymnasium as gym
+import numpy as np
+import torch
+from stable_baselines3 import PPO
+
+IDS = {"pendulum": "Pendulum-v1", "halfcheetah": "HalfCheetah-v5", "hopper": "Hopper-v5"}
+SEED0 = 10_000
+
+
+def main() -> int:
+    ap = argparse.ArgumentParser()
+    ap.add_argument("run", type=pathlib.Path)
+    ap.add_argument("out", type=pathlib.Path)
+    ap.add_argument("--episodes", type=int, default=20)
+    a = ap.parse_args()
+    torch.set_num_threads(1)
+
+    res = json.loads((a.run / "result.json").read_text())
+    env = gym.make(IDS[res["env"]])
+    model = PPO.load(a.run / "model.zip", device="cpu")
+
+    returns, lengths = [], []
+    t0 = time.time()
+    for k in range(a.episodes):
+        obs, _ = env.reset(seed=SEED0 + k)
+        done, ret, n = False, 0.0, 0
+        while not done:
+            act, _ = model.predict(obs, deterministic=True)
+            obs, r, term, trunc, _ = env.step(act)
+            ret += float(r)
+            n += 1
+            done = term or trunc
+        returns.append(ret)
+        lengths.append(n)
+
+    out = dict(
+        env=res["env"], fault=res["fault"], dose=res["dose"], seed=res["seed"],
+        weights_sha256=res["weights_sha256"], episodes=a.episodes,
+        returns=returns, lengths=lengths, mean=float(np.mean(returns)),
+        eval_s=round(time.time() - t0, 3),
+    )
+    a.out.mkdir(parents=True, exist_ok=True)
+    (a.out / "clean_eval.json").write_text(json.dumps(out))
+    print(json.dumps({k: out[k] for k in ("env", "fault", "dose", "seed", "mean", "eval_s")}))
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/experiments/e57-clean-eval/explore.py b/experiments/e57-clean-eval/explore.py
new file mode 100644
index 0000000..5372406
--- /dev/null
+++ b/experiments/e57-clean-eval/explore.py
@@ -0,0 +1,51 @@
+"""E57, exploratory (not in PROTOCOL.md): are the runs both curve checks miss
+shifted as a group, though no single one is harmed?
+
+    python explore.py [results]
+
+For each env and dose, the clean returns of boundary-fault runs that are
+silent on the curve, in units of the fault-free band (none, seeds 10-19):
+their mean z, and a two-sided Mann-Whitney U test against the 13 fault-free
+runs (seeds 0-2 and 10-19). Also the clean-return gap between each such run
+and the fault-free run at its own seed. Writes results/explore.txt.
+"""
+
+import csv
+import pathlib
+import statistics as st
+import sys
+
+from scipy.stats import mannwhitneyu
+
+HERE = pathlib.Path(__file__).resolve().parent
+
+
+def main() -> int:
+    root = pathlib.Path(sys.argv[1]) if len(sys.argv) > 1 else HERE / "results"
+    rows = list(csv.DictReader(open(root / "clean.csv")))
+    for r in rows:
+        r["seed"], r["clean"] = int(r["seed"]), float(r["clean"])
+    out = ["exploratory: boundary-fault runs silent on the curve, against fault-free runs",
+           "env          dose    n   mean z   median z   U-test p   twin gap median (clean - none at same seed)"]
+    for env in sorted({r["env"] for r in rows}):
+        band = [r["clean"] for r in rows if r["env"] == env and r["fault"] == "none" and r["seed"] >= 10]
+        mu, sd = st.mean(band), st.stdev(band)
+        free = [r["clean"] for r in rows if r["env"] == env and r["fault"] == "none"]
+        twin = {r["seed"]: r["clean"] for r in rows if r["env"] == env and r["fault"] == "none"}
+        for dose in ("one", "0.001", "0.01", "0.1", "1.0"):
+            s = [r for r in rows if r["env"] == env and r["dose"] == dose and r["kind"] == "boundary"
+                 and r["seed"] < 10 and r["silent_curve"] == "1"]
+            if not s:
+                continue
+            z = [(r["clean"] - mu) / sd for r in s]
+            p = mannwhitneyu([r["clean"] for r in s], free, alternative="two-sided").pvalue
+            gap = st.median(r["clean"] - twin[r["seed"]] for r in s)
+            out.append(f"{env:12} {dose:6} {len(s):3}   {st.mean(z):6.2f}   {st.median(z):8.2f}   {p:8.3f}   {gap:9.1f}")
+    text = "\n".join(out)
+    (root / "explore.txt").write_text(text + "\n")
+    print(text)
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/experiments/e57-clean-eval/results/clean.csv b/experiments/e57-clean-eval/results/clean.csv
new file mode 100644
index 0000000..9b299c8
--- /dev/null
+++ b/experiments/e57-clean-eval/results/clean.csv
@@ -0,0 +1,835 @@
+env,fault,dose,seed,kind,episodes,clean,harmed,rule,strict,silent_curve,last,log_error,sha
+halfcheetah,action:clip,0.01,0,boundary,50,1131.19,0,0,0,1,706.5,-424.69,ec5a179d
+halfcheetah,action:clip,0.01,1,boundary,50,835.7,0,0,0,1,258.8,-576.9,7eceb0cc
+halfcheetah,action:clip,0.01,2,boundary,50,971.14,0,0,0,1,578.3,-392.84,35ecae43
+halfcheetah,action:clip,1.0,0,boundary,50,-234.69,1,0,1,0,1118.5,1353.19,8ee6a77d
+halfcheetah,action:clip,1.0,1,boundary,50,-269.26,1,0,1,0,1148.4,1417.66,14847897
+halfcheetah,action:clip,1.0,2,boundary,50,-360.08,1,0,1,0,994.4,1354.48,ff882cd9
+halfcheetah,action:clip,one,0,boundary,50,926.03,0,0,0,1,476.1,-449.93,f7759731
+halfcheetah,action:clip,one,1,boundary,50,842.94,0,0,0,1,577.7,-265.24,cf4d7c9a
+halfcheetah,action:clip,one,2,boundary,50,849.95,0,0,0,1,710.8,-139.15,9f06912c
+halfcheetah,action:f16,0.01,0,boundary,50,920.49,0,0,0,1,526.4,-394.09,a01811f5
+halfcheetah,action:f16,0.01,1,boundary,50,1027.76,0,0,0,1,624.9,-402.86,fbd338e0
+halfcheetah,action:f16,0.01,2,boundary,50,734.64,0,0,0,1,590.0,-144.64,01547561
+halfcheetah,action:f16,1.0,0,boundary,50,941.44,0,0,0,1,575.9,-365.54,bf57cc96
+halfcheetah,action:f16,1.0,1,boundary,50,1050.5,0,0,0,1,594.4,-456.1,ae75b2d6
+halfcheetah,action:f16,1.0,2,boundary,50,842.72,0,0,0,1,507.9,-334.82,00ec2a01
+halfcheetah,action:f16,one,0,boundary,50,1000.49,0,0,0,1,500.7,-499.79,91d85ccb
+halfcheetah,action:f16,one,1,boundary,50,782.65,0,0,0,1,488.8,-293.85,4014b47b
+halfcheetah,action:f16,one,2,boundary,50,1191.03,0,0,0,1,818.1,-372.93,f3b2bad8
+halfcheetah,action:stale,0.01,0,boundary,50,879.57,0,0,0,1,537.5,-342.07,b0751b3a
+halfcheetah,action:stale,0.01,1,boundary,50,1043.57,0,0,0,1,616.0,-427.57,41460c07
+halfcheetah,action:stale,0.01,2,boundary,50,660.89,0,0,0,1,553.2,-107.69,a25b31ba
+halfcheetah,action:stale,1.0,0,boundary,50,419.45,0,0,1,0,30.5,-388.95,e3802a5d
+halfcheetah,action:stale,1.0,1,boundary,50,370.58,0,0,0,1,254.4,-116.18,dd17a435
+halfcheetah,action:stale,1.0,2,boundary,50,733.52,0,0,0,1,402.8,-330.72,74196379
+halfcheetah,action:stale,one,0,boundary,50,797.6,0,0,0,1,328.4,-469.2,63d03276
+halfcheetah,action:stale,one,1,boundary,50,1160.24,0,0,0,1,605.8,-554.44,7e1a788a
+halfcheetah,action:stale,one,2,boundary,50,958.32,0,0,0,1,661.6,-296.72,db4fec84
+halfcheetah,action:swap,0.01,0,boundary,50,641.77,0,0,0,1,356.2,-285.57,21898a3c
+halfcheetah,action:swap,0.01,1,boundary,50,981.74,0,0,0,1,595.5,-386.24,90971b4a
+halfcheetah,action:swap,0.01,2,boundary,50,841.9,0,0,0,1,530.4,-311.5,50bf08ce
+halfcheetah,action:swap,1.0,0,boundary,50,-398.64,1,1,1,0,-360.2,38.44,a46e0958
+halfcheetah,action:swap,1.0,1,boundary,50,-608.15,1,1,1,0,-366.4,241.75,03050f8b
+halfcheetah,action:swap,1.0,2,boundary,50,-322.58,1,1,1,0,-334.6,-12.02,33392cdc
+halfcheetah,action:swap,one,0,boundary,50,919.89,0,0,0,1,503.2,-416.69,ef171afa
+halfcheetah,action:swap,one,1,boundary,50,1518.52,0,0,0,1,616.1,-902.42,5e7659c6
+halfcheetah,action:swap,one,2,boundary,50,1090.05,0,0,0,1,611.7,-478.35,47c3f841
+halfcheetah,action:zero,0.01,0,boundary,50,901.43,0,0,0,1,517.0,-384.43,562a50ad
+halfcheetah,action:zero,0.01,1,boundary,50,694.46,0,0,0,1,290.0,-404.46,d1cddc03
+halfcheetah,action:zero,0.01,2,boundary,50,1034.41,0,0,0,1,561.0,-473.41,bf2c4b43
+halfcheetah,action:zero,1.0,0,boundary,50,-463.52,1,1,1,0,-0.1,463.42,71e141b6
+halfcheetah,action:zero,1.0,1,boundary,50,-1521.24,1,1,1,0,-0.1,1521.14,50e349ce
+halfcheetah,action:zero,1.0,2,boundary,50,-1213.03,1,1,1,0,-0.1,1212.93,34d1323f
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diff --git a/experiments/e57-clean-eval/results/e57-src.sha256 b/experiments/e57-clean-eval/results/e57-src.sha256
new file mode 100644
index 0000000..4fb0195
--- /dev/null
+++ b/experiments/e57-clean-eval/results/e57-src.sha256
@@ -0,0 +1,2 @@
+277daf21ebd4d4b066dad5a800fa4b0f2af43e7d352d5a5af1655e3480272e0b  evaluate.py
+9cbe443184dc3b89fb5f77bfe06373a201590f51859b8c92e6569f0435e20501  summarise.py
diff --git a/experiments/e57-clean-eval/results/explore.txt b/experiments/e57-clean-eval/results/explore.txt
new file mode 100644
index 0000000..458df73
--- /dev/null
+++ b/experiments/e57-clean-eval/results/explore.txt
@@ -0,0 +1,13 @@
+exploratory: boundary-fault runs silent on the curve, against fault-free runs
+env          dose    n   mean z   median z   U-test p   twin gap median (clean - none at same seed)
+halfcheetah  one     60     0.56       0.51      0.096       100.7
+halfcheetah  0.01    57     0.43       0.55      0.139        80.0
+halfcheetah  1.0     31     0.28       0.41      0.571        63.0
+hopper       one     69     0.19       0.62      0.534       142.4
+hopper       0.01    66     0.16       0.67      0.539       168.3
+hopper       1.0     35     0.27       0.81      0.342       368.2
+pendulum     one     63     0.24       0.55      0.195         6.8
+pendulum     0.001   58     0.03       0.60      0.053         6.5
+pendulum     0.01    59     0.09       0.54      0.208         7.3
+pendulum     0.1     50     0.36       0.60      0.061         8.4
+pendulum     1.0     25     0.65       0.68      0.003         9.2
diff --git a/experiments/e57-clean-eval/results/jobs.txt b/experiments/e57-clean-eval/results/jobs.txt
new file mode 100644
index 0000000..295da0e
--- /dev/null
+++ b/experiments/e57-clean-eval/results/jobs.txt
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diff --git a/experiments/e57-clean-eval/results/load.txt b/experiments/e57-clean-eval/results/load.txt
new file mode 100644
index 0000000..9aebb6d
--- /dev/null
+++ b/experiments/e57-clean-eval/results/load.txt
@@ -0,0 +1,2 @@
+ 00:16:58 up 28 days, 13:18,  1 user,  load average: 0.37, 0.25, 0.31
+ 00:22:43 up 28 days, 13:24,  1 user,  load average: 12.06, 8.48, 4.03
diff --git a/experiments/e57-clean-eval/results/pilot/e54-boundary-faults_results_halfcheetah_none_1.0_seed0/clean_eval.json b/experiments/e57-clean-eval/results/pilot/e54-boundary-faults_results_halfcheetah_none_1.0_seed0/clean_eval.json
new file mode 100644
index 0000000..f955b4d
--- /dev/null
+++ b/experiments/e57-clean-eval/results/pilot/e54-boundary-faults_results_halfcheetah_none_1.0_seed0/clean_eval.json
@@ -0,0 +1 @@
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diff --git a/experiments/e57-clean-eval/results/pilot/e54-boundary-faults_results_halfcheetah_none_1.0_seed10/clean_eval.json b/experiments/e57-clean-eval/results/pilot/e54-boundary-faults_results_halfcheetah_none_1.0_seed10/clean_eval.json
new file mode 100644
index 0000000..82d118f
--- /dev/null
+++ b/experiments/e57-clean-eval/results/pilot/e54-boundary-faults_results_halfcheetah_none_1.0_seed10/clean_eval.json
@@ -0,0 +1 @@
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diff --git a/experiments/e57-clean-eval/results/pilot/e54-boundary-faults_results_halfcheetah_obs__f16_1.0_seed0/clean_eval.json b/experiments/e57-clean-eval/results/pilot/e54-boundary-faults_results_halfcheetah_obs__f16_1.0_seed0/clean_eval.json
new file mode 100644
index 0000000..36ec06c
--- /dev/null
+++ b/experiments/e57-clean-eval/results/pilot/e54-boundary-faults_results_halfcheetah_obs__f16_1.0_seed0/clean_eval.json
@@ -0,0 +1 @@
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diff --git a/experiments/e57-clean-eval/results/pilot/e54-boundary-faults_results_pendulum_none_1.0_seed0/clean_eval.json b/experiments/e57-clean-eval/results/pilot/e54-boundary-faults_results_pendulum_none_1.0_seed0/clean_eval.json
new file mode 100644
index 0000000..c3e7439
--- /dev/null
+++ b/experiments/e57-clean-eval/results/pilot/e54-boundary-faults_results_pendulum_none_1.0_seed0/clean_eval.json
@@ -0,0 +1 @@
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diff --git a/experiments/e57-clean-eval/results/pilot/e54-boundary-faults_results_pendulum_none_1.0_seed10/clean_eval.json b/experiments/e57-clean-eval/results/pilot/e54-boundary-faults_results_pendulum_none_1.0_seed10/clean_eval.json
new file mode 100644
index 0000000..b9127d9
--- /dev/null
+++ b/experiments/e57-clean-eval/results/pilot/e54-boundary-faults_results_pendulum_none_1.0_seed10/clean_eval.json
@@ -0,0 +1 @@
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diff --git a/experiments/e57-clean-eval/results/pilot/e54-boundary-faults_results_pendulum_obs__f16_1.0_seed0/clean_eval.json b/experiments/e57-clean-eval/results/pilot/e54-boundary-faults_results_pendulum_obs__f16_1.0_seed0/clean_eval.json
new file mode 100644
index 0000000..4748b18
--- /dev/null
+++ b/experiments/e57-clean-eval/results/pilot/e54-boundary-faults_results_pendulum_obs__f16_1.0_seed0/clean_eval.json
@@ -0,0 +1 @@
+{"env": "pendulum", "fault": "obs:f16", "dose": "1.0", "seed": 0, "weights_sha256": "6bd93edb7230cacb85550b44354f730ce295ba935b79400d7b0a0eee27feb54c", "episodes": 20, "returns": [-0.6148502847222538, -132.41961828831072, -135.25942367129457, -131.76644471085925, -266.83810574873667, -127.97829042128303, -273.76599189561944, -139.17173076058464, -136.09559530010796, -0.8128044903542682, -249.30802416340077, -0.6422430478390052, -251.32060725199315, -1.5906682832198593, -282.7034127005091, -0.5700696343421382, -261.2770329685088, -135.59073490063162, -132.7067860869225, -133.57138538569802], "lengths": [200, 200, 200, 200, 200, 200, 200, 200, 200, 200, 200, 200, 200, 200, 200, 200, 200, 200, 200, 200], "mean": -139.7001909997469, "eval_s": 0.292}
\ No newline at end of file
diff --git a/experiments/e57-clean-eval/results/pilot/e56-hopper-faults_results_hopper_none_1.0_seed0/clean_eval.json b/experiments/e57-clean-eval/results/pilot/e56-hopper-faults_results_hopper_none_1.0_seed0/clean_eval.json
new file mode 100644
index 0000000..1491ad7
--- /dev/null
+++ b/experiments/e57-clean-eval/results/pilot/e56-hopper-faults_results_hopper_none_1.0_seed0/clean_eval.json
@@ -0,0 +1 @@
+{"env": "hopper", "fault": "none", "dose": "1.0", "seed": 0, "weights_sha256": "13daa0142e18b9b947cc1f947014d6e46222902b7e92751a277bd271f745a0ef", "episodes": 20, "returns": [3535.660787262251, 3553.1947064922574, 2317.175320043081, 3540.1566842578504, 3543.777768352139, 3551.4380178924816, 3554.7992593801555, 2450.7444275937023, 3557.471994373874, 3555.7826748504667, 3566.675281385641, 3561.5672199772544, 3165.5111868620806, 3563.062375718484, 3559.8602567082185, 3564.547527405282, 3550.415193343448, 2585.3148668086537, 3551.056190629265, 3549.79485945411], "lengths": [1000, 1000, 612, 1000, 1000, 1000, 1000, 654, 1000, 1000, 1000, 1000, 842, 1000, 1000, 1000, 1000, 684, 1000, 1000], "mean": 3368.9003299395345, "eval_s": 2.388}
\ No newline at end of file
diff --git a/experiments/e57-clean-eval/results/pilot/e56-hopper-faults_results_hopper_none_1.0_seed10/clean_eval.json b/experiments/e57-clean-eval/results/pilot/e56-hopper-faults_results_hopper_none_1.0_seed10/clean_eval.json
new file mode 100644
index 0000000..de2e412
--- /dev/null
+++ b/experiments/e57-clean-eval/results/pilot/e56-hopper-faults_results_hopper_none_1.0_seed10/clean_eval.json
@@ -0,0 +1 @@
+{"env": "hopper", "fault": "none", "dose": "1.0", "seed": 10, "weights_sha256": "d5a3ae295d1210de734820e1c0749cceb8b96dac1c772c88decf2f1087070059", "episodes": 20, "returns": [3655.3590510916865, 3644.4871137657647, 3655.728741264313, 3661.9561155117226, 3624.861410819209, 3635.8586701972695, 3631.335030254979, 3650.8436597907303, 3652.747050004136, 3654.6272943409763, 3660.238657064603, 3656.8643740073194, 3655.8339245776524, 3660.677531334535, 3656.7611321078543, 3642.555571671143, 3660.6933156673626, 3657.475136328713, 3647.7388874930575, 3658.4614451449943], "lengths": [1000, 1000, 1000, 1000, 1000, 1000, 1000, 1000, 1000, 1000, 1000, 1000, 1000, 1000, 1000, 1000, 1000, 1000, 1000, 1000], "mean": 3651.2552056219006, "eval_s": 2.546}
\ No newline at end of file
diff --git a/experiments/e57-clean-eval/results/pilot/e56-hopper-faults_results_hopper_obs__f16_1.0_seed0/clean_eval.json b/experiments/e57-clean-eval/results/pilot/e56-hopper-faults_results_hopper_obs__f16_1.0_seed0/clean_eval.json
new file mode 100644
index 0000000..0a7b7da
--- /dev/null
+++ b/experiments/e57-clean-eval/results/pilot/e56-hopper-faults_results_hopper_obs__f16_1.0_seed0/clean_eval.json
@@ -0,0 +1 @@
+{"env": "hopper", "fault": "obs:f16", "dose": "1.0", "seed": 0, "weights_sha256": "0b88c98ace320426c458bd2e94e8459b82fedb6e663014b44a748d617b1c2cc5", "episodes": 20, "returns": [1185.3575695364227, 1449.1056958741244, 1453.5602127413536, 1252.0261061462352, 1468.015830852532, 1290.881145498214, 1285.2192677014775, 3356.463267298476, 1220.4963692535464, 1309.4698936381449, 1490.3647389104456, 1453.3022586372335, 1701.0866609159627, 1201.7808588855692, 1541.3838549545537, 2692.9326962402884, 1410.631657584418, 2586.1661345431985, 1840.5422086839878, 1480.9880026293386], "lengths": [362, 419, 420, 377, 424, 385, 384, 1000, 371, 391, 432, 419, 495, 366, 447, 805, 410, 743, 553, 430], "mean": 1633.488721526276, "eval_s": 1.221}
\ No newline at end of file
diff --git a/experiments/e57-clean-eval/results/registered.out b/experiments/e57-clean-eval/results/registered.out
new file mode 100644
index 0000000..9c35597
--- /dev/null
+++ b/experiments/e57-clean-eval/results/registered.out
@@ -0,0 +1,3 @@
+ 00:16:58 up 28 days, 13:18,  1 user,  load average: 0.37, 0.25, 0.31
+834 runs, 12 at a time
+E57_DONE
diff --git a/experiments/e57-clean-eval/results/summary.txt b/experiments/e57-clean-eval/results/summary.txt
new file mode 100644
index 0000000..50a52b0
--- /dev/null
+++ b/experiments/e57-clean-eval/results/summary.txt
@@ -0,0 +1,29 @@
+halfcheetah: band (none, seeds 10-19) mean 852.6 sd 202.5 n 10; harm bar 245.1; band seeds flagged against the other nine: 0 of 10
+hopper: band (none, seeds 10-19) mean 2717.4 sd 857.0 n 10; harm bar 146.5; band seeds flagged against the other nine: 0 of 10
+pendulum: band (none, seeds 10-19) mean -185.9 sd 26.1 n 10; harm bar -264.1; band seeds flagged against the other nine: 0 of 10
+
+boundary-fault runs, seeds 0-2: harmed / runs; harmed among those silent on the curve
+  halfcheetah  one    harmed   0/63  silent on the curve  60, of them harmed   0
+  halfcheetah  0.01   harmed   0/63  silent on the curve  57, of them harmed   0
+  halfcheetah  1.0    harmed  28/63  silent on the curve  31, of them harmed   0
+  hopper       one    harmed   0/69  silent on the curve  69, of them harmed   0
+  hopper       0.01   harmed   0/69  silent on the curve  66, of them harmed   0
+  hopper       1.0    harmed  19/69  silent on the curve  35, of them harmed   0
+  pendulum     one    harmed   1/63  silent on the curve  63, of them harmed   1
+  pendulum     0.001  harmed   2/63  silent on the curve  58, of them harmed   1
+  pendulum     0.01   harmed   1/63  silent on the curve  59, of them harmed   1
+  pendulum     0.1    harmed   6/63  silent on the curve  50, of them harmed   2
+  pendulum     1.0    harmed  24/63  silent on the curve  25, of them harmed   0
+
+faults silent on the curve at all three seeds and harmed at two or more (fault, dose: clean returns)
+
+log error (logged final return - clean return): min / median / max by kind
+  halfcheetah  control   n  13     -479.1    -410.4     126.6
+  halfcheetah  boundary  n 177    -1034.8    -377.7    1521.1
+  halfcheetah  log       n  18     -441.1    -331.5    -259.1
+  hopper       control   n  19    -1666.7    -439.8     805.9
+  hopper       boundary  n 201    -1959.9   -1129.5    1162.5
+  hopper       log       n  18    -1667.7    -333.4     489.1
+  pendulum     control   n  19      -70.0     -35.2      33.3
+  pendulum     boundary  n 309     -450.6     -29.0    1639.4
+  pendulum     log       n  30      -70.0     -34.2       4.0
diff --git a/experiments/e57-clean-eval/results/verdicts.txt b/experiments/e57-clean-eval/results/verdicts.txt
new file mode 100644
index 0000000..48b04ee
--- /dev/null
+++ b/experiments/e57-clean-eval/results/verdicts.txt
@@ -0,0 +1,6 @@
+V1: holds - 834 evaluations of 834 runs, 834 with 50 episodes
+V2: holds - 12 weights shared by two or more runs; 0 with differing clean returns []
+P1: holds - band seeds flagged: {'halfcheetah': 0, 'hopper': 0, 'pendulum': 0}
+P2: holds - harmed at one value (harmed, runs): {'halfcheetah': (0, 63), 'hopper': (0, 69), 'pendulum': (1, 63)}
+P3: holds - pendulum reward:zero 1.0: [(0, -1195.55, '0.0', 1), (1, -1549.63, '0.0', 1), (2, -1639.38, '0.0', 1)]
+reported: hopper obs:f16 1.0 (seed, clean, harmed, silent on the curve): [(0, 1505.25, 0, '1'), (1, 3588.14, 0, '1'), (2, 3592.49, 0, '1')]
diff --git a/experiments/e57-clean-eval/run.sh b/experiments/e57-clean-eval/run.sh
new file mode 100644
index 0000000..839d323
--- /dev/null
+++ b/experiments/e57-clean-eval/run.sh
@@ -0,0 +1,21 @@
+#!/usr/bin/env bash
+# E57 on guangzhao: evaluate every E54 and E56 final policy on a clean
+# environment, 12 at a time. Writes results/<env>/<fault>/<dose>/seed<s>/clean_eval.json.
+#   bash run.sh
+set -uo pipefail
+export OMP_NUM_THREADS=1
+PY="$HOME/zuogou/plugrl/bridges-venv/bin/python"
+cd "$(dirname "$0")"
+mkdir -p results
+find ../e54-boundary-faults/results ../e56-hopper-faults/results -name model.zip \
+  -not -path '*/pilot/*' -printf '%h\n' | sort > results/jobs.txt
+sha256sum evaluate.py summarise.py > results/e57-src.sha256
+uptime | tee results/load.txt
+echo "$(wc -l < results/jobs.txt) runs, 12 at a time"
+xargs -P 12 -I{} sh -c '
+  r="$1"; rel="${r#*/results/}"
+  "$0" evaluate.py "$r" "results/$rel" --episodes 50 > /dev/null 2> "results/$(echo "$rel" | tr / _).err" \
+    && rm -f "results/$(echo "$rel" | tr / _).err" || echo "failed: $r"
+' "$PY" {} < results/jobs.txt
+uptime >> results/load.txt
+echo E57_DONE
diff --git a/experiments/e57-clean-eval/summarise.py b/experiments/e57-clean-eval/summarise.py
new file mode 100644
index 0000000..8df63c3
--- /dev/null
+++ b/experiments/e57-clean-eval/summarise.py
@@ -0,0 +1,120 @@
+"""E57: join every clean evaluation with E54's and E56's runs.csv, and count.
+
+    python summarise.py [results]
+
+Writes results/clean.csv (one row per run) and results/summary.txt.
+"""
+
+import csv
+import json
+import pathlib
+import statistics as st
+import sys
+
+HERE = pathlib.Path(__file__).resolve().parent
+RUNS = [HERE.parent / "e54-boundary-faults/results/runs.csv",
+        HERE.parent / "e56-hopper-faults/results/runs.csv"]
+CONTROLS = {"none", "delay-1ms", "wire-float64"}
+LOUD = {"indices:reorder", "reward:short-array"}
+
+
+def kind(fault: str) -> str:
+    if fault in CONTROLS:
+        return "control"
+    if fault in LOUD:
+        return "loud"
+    if fault.startswith("log:"):
+        return "log"
+    return "boundary"
+
+
+def load(root: pathlib.Path) -> list[dict]:
+    trained = {}
+    for path in RUNS:
+        for r in csv.DictReader(open(path)):
+            trained[(r["env"], r["fault"], r["dose"], int(r["seed"]))] = r
+    rows = []
+    for f in sorted(root.glob("*/*/*/seed*/clean_eval.json")):
+        d = json.loads(f.read_text())
+        t = trained[(d["env"], d["fault"], d["dose"], int(d["seed"]))]
+        rows.append(dict(
+            env=d["env"], fault=d["fault"], dose=d["dose"], seed=int(d["seed"]), kind=kind(d["fault"]),
+            episodes=d["episodes"], clean=round(d["mean"], 2), sha=d["weights_sha256"][:8],
+            # The loud faults' runs have no `strict` (no return was logged); see AMENDMENT.md.
+            rule=int(t["rule"]) if t["rule"] else None, strict=int(t["strict"]) if t["strict"] else None,
+            last=float(t["last"]) if t["last"] else None,
+        ))
+    return rows
+
+
+def judge(rows: list[dict]) -> dict:
+    """Band per env (none, seeds 10-19); harmed = more than 3 s.d. below its mean."""
+    bands = {}
+    for env in sorted({r["env"] for r in rows}):
+        band = [r for r in rows if r["env"] == env and r["fault"] == "none" and r["seed"] >= 10]
+        vals = [r["clean"] for r in band]
+        bands[env] = dict(mean=st.mean(vals), sd=st.stdev(vals), n=len(vals))
+        # Each band seed judged against the other nine.
+        for r in band:
+            rest = [x["clean"] for x in band if x is not r]
+            r["harmed"] = int(r["clean"] < st.mean(rest) - 3 * st.stdev(rest))
+    for r in rows:
+        if "harmed" not in r:
+            b = bands[r["env"]]
+            r["harmed"] = int(r["clean"] < b["mean"] - 3 * b["sd"])
+        r["silent_curve"] = int(r["rule"] == 0 and r["strict"] == 0)
+        r["log_error"] = None if r["last"] is None else round(r["last"] - r["clean"], 2)
+    return bands
+
+
+def main() -> int:
+    root = pathlib.Path(sys.argv[1]) if len(sys.argv) > 1 else HERE / "results"
+    rows = load(root)
+    bands = judge(rows)
+    cols = ["env", "fault", "dose", "seed", "kind", "episodes", "clean", "harmed", "rule", "strict",
+            "silent_curve", "last", "log_error", "sha"]
+    with open(root / "clean.csv", "w", newline="") as fh:
+        w = csv.DictWriter(fh, fieldnames=cols, lineterminator="\n")
+        w.writeheader()
+        for r in rows:
+            w.writerow({k: r[k] for k in cols})
+
+    out = []
+    for env, b in bands.items():
+        flagged = sum(r["harmed"] for r in rows if r["env"] == env and r["fault"] == "none" and r["seed"] >= 10)
+        out.append(f"{env}: band (none, seeds 10-19) mean {b['mean']:.1f} sd {b['sd']:.1f} n {b['n']}; "
+                   f"harm bar {b['mean'] - 3 * b['sd']:.1f}; band seeds flagged against the other nine: {flagged} of 10")
+    out.append("")
+    out.append("boundary-fault runs, seeds 0-2: harmed / runs; harmed among those silent on the curve")
+    for env in bands:
+        for dose in ("one", "0.001", "0.01", "0.1", "1.0"):
+            d = [r for r in rows if r["env"] == env and r["dose"] == dose and r["kind"] == "boundary" and r["seed"] < 10]
+            if not d:
+                continue
+            s = [r for r in d if r["silent_curve"]]
+            out.append(f"  {env:12} {dose:6} harmed {sum(r['harmed'] for r in d):3}/{len(d):<3} "
+                       f"silent on the curve {len(s):3}, of them harmed {sum(r['harmed'] for r in s):3}")
+    out.append("")
+    out.append("faults silent on the curve at all three seeds and harmed at two or more (fault, dose: clean returns)")
+    for env in bands:
+        b = bands[env]
+        for (fault, dose) in sorted({(r["fault"], r["dose"]) for r in rows if r["env"] == env and r["kind"] == "boundary"}):
+            d = [r for r in rows if r["env"] == env and r["fault"] == fault and r["dose"] == dose and r["seed"] < 10]
+            if len(d) == 3 and all(r["silent_curve"] for r in d) and sum(r["harmed"] for r in d) >= 2:
+                z = [round((r["clean"] - b["mean"]) / b["sd"], 1) for r in d]
+                out.append(f"  {env:12} {fault:20} {dose:6} clean {[r['clean'] for r in d]}  in band s.d. {z}")
+    out.append("")
+    out.append("log error (logged final return - clean return): min / median / max by kind")
+    for env in bands:
+        for k in ("control", "boundary", "log"):
+            e = [r["log_error"] for r in rows if r["env"] == env and r["kind"] == k and r["log_error"] is not None]
+            if e:
+                out.append(f"  {env:12} {k:9} n {len(e):3}  {min(e):9.1f} {st.median(e):9.1f} {max(e):9.1f}")
+    text = "\n".join(out)
+    (root / "summary.txt").write_text(text + "\n")
+    print(text)
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/experiments/e57-clean-eval/verdicts.py b/experiments/e57-clean-eval/verdicts.py
new file mode 100644
index 0000000..12de40b
--- /dev/null
+++ b/experiments/e57-clean-eval/verdicts.py
@@ -0,0 +1,62 @@
+"""E57: judge PROTOCOL.md's checks and predictions from results/clean.csv.
+
+    python verdicts.py [results]      # prints, and writes results/verdicts.txt
+"""
+
+import csv
+import pathlib
+import sys
+from collections import defaultdict
+
+HERE = pathlib.Path(__file__).resolve().parent
+
+
+def main() -> int:
+    root = pathlib.Path(sys.argv[1]) if len(sys.argv) > 1 else HERE / "results"
+    rows = list(csv.DictReader(open(root / "clean.csv")))
+    for r in rows:
+        r["seed"], r["harmed"], r["episodes"] = int(r["seed"]), int(r["harmed"]), int(r["episodes"])
+        r["clean"] = float(r["clean"])
+    out = []
+
+    jobs = (root / "jobs.txt").read_text().split()
+    full = sum(r["episodes"] == 50 for r in rows)
+    out.append(f"V1: {'holds' if full == len(jobs) == len(rows) else 'FAILS'} - "
+               f"{len(rows)} evaluations of {len(jobs)} runs, {full} with 50 episodes")
+
+    by_sha = defaultdict(set)
+    for r in rows:
+        by_sha[(r["env"], r["sha"])].add(r["clean"])
+    shared = [k for k in by_sha if sum(1 for r in rows if (r["env"], r["sha"]) == k) > 1]
+    bad = [k for k in shared if len(by_sha[k]) > 1]
+    out.append(f"V2: {'holds' if not bad else 'FAILS'} - {len(shared)} weights shared by two or more runs; "
+               f"{len(bad)} with differing clean returns {bad[:5]}")
+
+    p1 = {}
+    for env in sorted({r["env"] for r in rows}):
+        p1[env] = sum(r["harmed"] for r in rows if r["env"] == env and r["fault"] == "none" and r["seed"] >= 10)
+    out.append(f"P1: {'holds' if max(p1.values()) <= 1 else 'FALSIFIED'} - band seeds flagged: {p1}")
+
+    p2 = {}
+    for env in sorted({r["env"] for r in rows}):
+        d = [r for r in rows if r["env"] == env and r["dose"] == "one" and r["kind"] == "boundary" and r["seed"] < 10]
+        p2[env] = (sum(r["harmed"] for r in d), len(d))
+    ok = all(h <= 0.10 * n for h, n in p2.values())
+    out.append(f"P2: {'holds' if ok else 'FALSIFIED'} - harmed at one value (harmed, runs): {p2}")
+
+    d = [r for r in rows if r["env"] == "pendulum" and r["fault"] == "reward:zero" and r["dose"] == "1.0" and r["seed"] < 10]
+    ok = len(d) == 3 and all(r["harmed"] for r in d) and all(r["last"] and float(r["last"]) == 0.0 for r in d)
+    out.append(f"P3: {'holds' if ok else 'FALSIFIED'} - pendulum reward:zero 1.0: "
+               f"{[(r['seed'], r['clean'], r['last'], r['harmed']) for r in d]}")
+
+    h = [r for r in rows if r["env"] == "hopper" and r["fault"] == "obs:f16" and r["dose"] == "1.0" and r["seed"] < 10]
+    out.append(f"reported: hopper obs:f16 1.0 (seed, clean, harmed, silent on the curve): "
+               f"{[(r['seed'], r['clean'], r['harmed'], r['silent_curve']) for r in h]}")
+    text = "\n".join(out)
+    (root / "verdicts.txt").write_text(text + "\n")
+    print(text)
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())