{
  "role": "code_methods_reviewer",
  "decision": "pass",
  "summary": "The implementation matches the locked registration: the registered contrast (observed 15+ mph vs below 10 mph), the five preregistered position outcomes, the specified controls (week/season fixed effects, air temperature, home/away team fixed effects), and the registered uncertainty methods (4,000 game-level bootstrap draws plus HC3 robust OLS intervals with Holm correction across the outcome family) are all present and internally consistent. Sample gates (101 condition, 806 control, 907 comparable games) clear the preregistered floors of 100 and 750. Missingness is reconciled (2,127 input rows, 1,220 excluded as outside the registered contrast or incomplete, 1 missing weekly position scoring), and per-outcome denominators show zero undefined games among the 907 comparable games. Temporal handling is sound: observed postgame weather is used only to define retrospective comparison groups, the article explicitly disclaims forecast use, and the weather source lag through 2024 is handled by the registered stop-at-latest-available-season policy, which also satisfies the freshness minimum of 2024. Reproducibility is evidenced by deterministic SHA-256-derived bootstrap seed labels and two complete executions producing identical result hashes. All required outputs (table, figure, claim ledger, provenance receipts, artifact hashes) are present, and article numbers match the analysis JSON.",
  "findings": [
    {
      "severity": "warning",
      "check": "claim_consistency",
      "evidence": "article.blocks[1].text; analysis.effects[3].holm_adjusted_p; analysis.effects[4].holm_adjusted_p",
      "recommendation": "The article describes TE and kicker results as a 'supported difference' while their Holm-adjusted p-values (0.129) exceed 0.05. The article does disclose this tension explicitly and lists it in limitations, so it is not a misrepresentation, but 'supported' is a strong word for a result that is not statistically significant after multiplicity correction. Prefer 'interval excludes zero but not significant after Holm correction' phrasing in the lead and dek."
    },
    {
      "severity": "warning",
      "check": "uncertainty_consistency",
      "evidence": "analysis.effects[2].bootstrap_ci_95_lower=-9.38, bootstrap_ci_95_upper=-1.31, bootstrap_p_value=0.0105 vs adjusted_ci_95_lower=-6.98, adjusted_ci_95_upper=1.78, p_value=0.245",
      "recommendation": "For the WR outcome, the bootstrap interval excludes zero and the bootstrap p-value is 0.0105, while the HC3 model interval includes zero with p=0.245. Both intervals are reported as registered, and the article relies on the model-based interval, but the divergence between bootstrap and parametric uncertainty for WR is large enough that the article's 'not supported' framing for WR rests on one of two reported methods. A brief note acknowledging the bootstrap interval for WR would make the framing more transparent."
    },
    {
      "severity": "warning",
      "check": "missingness_reporting",
      "evidence": "analysis.research_audit.missingness.missing_by_field={outside_registered_contrast_or_incomplete: 1220, weekly_position_scoring: 1}",
      "recommendation": "The 1,220 excluded rows are aggregated into a single 'outside_registered_contrast_or_incomplete' category, so the relative contribution of the 10-15 mph excluded band versus incomplete scoring cannot be distinguished from the bundle alone. This is consistent with the registered contrast design (which excludes the 10-15 mph band by construction), but a finer breakdown would strengthen the missingness audit."
    }
  ],
  "artifacts_reviewed": [
    "analysis.json",
    "article-draft.json",
    "article.md",
    "claim-ledger.json",
    "data/registration.json",
    "data/reproducibility.json",
    "data/results.json",
    "data/study-effects.csv",
    "data/study-decisions.json",
    "data/station-agreement.json",
    "data/weekly-position-coverage.json",
    "figures/weather-position-effects-effects.png",
    "generated/analysis.py",
    "provenance.json",
    "research-registration.json"
  ],
  "model": "z-ai/glm-5.3",
  "created_at": "2026-09-03T10:33:03.881293+00:00"
}