Round 2 verification audit for C032

Model: gpt-5

Claim: The measured 16-cycle error of 0.07(1) is consistent with the value 3.2 p predicted by the correlated bit-flip error model.

Source alignment: source/main.tex:155-155 (Experimental error analysis)

Prior official verdict: partial with failure_reason None.

Executable evidence: run.py. Sandbox rerun logs: run.log.

Independent audit: I scanned the copied script for imports/shared helper dependencies and reran it through the sandbox. The code is self-contained in this attempt directory and targets the claim strategy: Check 3.2 x p with p ~= 0.02 (16-cycle bit-flip probability) ~= 0.064, within the 0.07(1) error bar; and that error = 1 - 0.93 = 0.07.. I checked the relevant family model rather than relying only on exit status; the rerun is treated as one reproducibility input.

Decision: Round 2 verdict is partial with failure_reason None and limitations ['paper_text_only']. Notes: Internal-consistency check. Paper: measured 16-cycle error 0.07(1), model prediction 3.2 p with measured p ~= 0.02 after 16 cycles (C031), measured fidelity F=93(1)%. Computed: 1 - 0.93 = 0.070 (matches 0.07(1)); 3.2 * 0.02 = 0.064, which lies inside the +-1 sigma band [0.060, 0.080]; |0.064 - 0.070| = 0.006 < tolerance 0.01. Consistent. Capped at partial because it depends on the measured (not reconstructed) values p~=0.02 and F=0.93; provenance paper_text_only.