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
0Unique collaborators
1/1OpenAlex citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5021119424
ORCID evidence
Observed aliases (2)
- Luke Allen (openalex, provider refresh)
- Luke N Allen (openalex, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Governance: 1 paper
- Human Ai Collab: 1 paper
- Labor Markets: 1 paper
- Productivity: 1 paper
Claim outcomes
- Ai Safety And Ethics: 1 paper
- Decision Quality: 1 paper
- Research Productivity: 1 paper
- Task Completion Time: 1 paper
- Consumer Welfare: 1 paper
- Employment: 1 paper
- Firm Revenue: 1 paper
- Governance And Regulation: 1 paper
- Inequality: 1 paper
- Market Structure: 1 paper
- Output Quality: 1 paper
- Skill Obsolescence: 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 |
|---|---|---|---|
| Generative AI can make clinicians faster and improve diagnostic suggestions, but real-world benefits are uncertain: hallucinations, bias, liability gaps and perverse incentives could offset gains unless deployment, payment and regulation are carefully designed.openalex | Luke N Allen orcid |
2026-03-09 | 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.