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
1/1OpenAlex citation coverage
Publication dates unavailable. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5050108279
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Gafrinda Kautsari (openalex, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Productivity: 1 paper
Claim outcomes
- Output Quality: 1 paper
- Research Productivity: 1 paper
- Consumer Welfare: 1 paper
- Decision Quality: 1 paper
- Task Completion Time: 1 paper
Papers in the OpenAlex view
Latest stored OpenAlex 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 |
|---|---|---|---|
| AI systems detect gastrointestinal bleeding lesions with high accuracy in retrospective studies and can speed clinician review, but there is scant prospective evidence that these diagnostic gains translate into better patient outcomes or cost-effectiveness, leaving economic value uncertain.semantic_scholar | Gafrinda Kautsari provider id |
Fetched 2026-03-15 | 0 |
Citation observation summary
OpenAlex 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.