R0050/2026-03-31/Q001/S03/R02¶
AI fact-checking and hedging research papers (batch rejection).
Summary¶
| Field | Value |
|---|---|
| Title | Various AI fact-checking papers |
| URL | Multiple arxiv.org URLs |
| Date accessed | 2026-03-31 |
| Publication date | 2025 |
| Author(s) | Various academic researchers |
| Publication | arXiv preprints |
Selection Decision¶
Included in evidence base: No
Rationale: These papers address AI/automated fact-checking confidence scores and uncertainty communication in machine learning systems. They do not document human journalistic methodology for calibrated uncertainty language. The batch includes papers on explaining uncertainty in automated fact-checking, scaling truth in AI fact-checking, and fact-checker requirements for explainable AI — all focused on technology, not journalistic practice standards.