Direction, evidence grade, and study type are AI-generated labels (gpt-5-mini), not human-verified. Syntheses are LLM-written. "Tensions" are machine-detected candidates, not confirmed contradictions. A research-acceleration tool, not peer review.
How this is built →
1Distinct papers
2Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2283838105
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Yu Chen (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Innovation: 1 paper
Claim outcomes
- Other: 1 paper
- Error Rate: 1 paper
- Task Completion Time: 1 paper
- Decision Quality: 1 paper
Papers in the Semantic Scholar view
Latest stored Semantic Scholar author observations only. Citation counts below are from the same provider and are not combined with other services.
Scroll the table horizontally to see every column.
| Paper | Author evidence | Date | Provider citations |
|---|---|---|---|
| AIVAT corrections plus time-uniform confidence sequences let evaluators stop agent-vs-agent poker comparisons far earlier without losing statistical validity; on 71k HUNL hands the method compresses variance by a median 54× and — under the asymptotic interval — cuts required hands by a median 74×, with an exact bounded-sample certificate available when a corrected-payoff bound is supplied.arxiv | Yu Chen provider id |
2026-08-06 | 1 |
Citation observation summary
Semantic Scholar supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 1 cumulative citations. This is a coverage summary, not an author score or h-index.