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
1Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2150851705
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Dimeji AbdulSobur Olawuyi (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Governance: 1 paper
Claim outcomes
- Ai Safety And Ethics: 1 paper
- Decision Quality: 1 paper
- Error Rate: 1 paper
- Governance And Regulation: 1 paper
- Task Allocation: 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 |
|---|---|---|---|
| Benchmark reveals hidden triage failures: three leading LLMs tested on 200 Nigerian primary-care vignettes each manifest distinct failure modes, and conventional safety metrics mask a 77-percentage-point under-triage in Llama 3.1 8B, implying model choice and deployment cost depend on local health-system priorities.arxiv | Dimeji AbdulSobur Olawuyi provider id |
2026-07-31 | 0 |
Citation observation summary
Semantic Scholar supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 0 cumulative citations. This is a coverage summary, not an author score or h-index.