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 span: 2025. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5079065563
ORCID evidence
Observed aliases (2)
- Ying Lu (openalex, provider refresh)
- Ying Lu (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Governance: 1 paper
- Human Ai Collab: 1 paper
- Org Design: 1 paper
Claim outcomes
- Worker Satisfaction: 1 paper
- Ai Safety And Ethics: 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 |
|---|---|---|---|
| Tailored explainable-AI boosts gig workers' acceptance, but too much explanation backfires: local or counterfactual reasons raise trust and improve manager-worker relations, while combining both overwhelms workers and reduces acceptance.openalex | Ying Lu provider id |
2025-12-09 | 6 |
Citation observation summary
OpenAlex supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 6 cumulative citations. This is a coverage summary, not an author score or h-index.