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
4Unique collaborators
1/1OpenAlex citation coverage
Publication dates unavailable. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5100701166
ORCID evidence
Observed aliases (1)
- Zhiwen Yu (openalex, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Human Ai Collab: 1 paper
- Labor Markets: 1 paper
- Productivity: 1 paper
Claim outcomes
- Output Quality: 1 paper
- Task Allocation: 1 paper
- Adoption Rate: 1 paper
- Firm Productivity: 1 paper
- Organizational Efficiency: 1 paper
- Other: 1 paper
- Regulatory Compliance: 1 paper
- Skill Acquisition: 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 |
|---|---|---|---|
| A Human–AI team can deliver near-expert online diagnoses while cutting required doctor involvement to roughly one-tenth; hierarchical reinforcement learning allocates human attention sparingly to preserve accuracy and lower labor per consultation.semantic_scholar | Zhiwen Yu orcid |
Fetched 2026-03-18 | 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.