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
1/1OpenAlex citation coverage
Publication dates unavailable. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5123774722
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Zhicheng Yu (openalex, provider refresh)
Topics and outcomes in this view
Assessment themes
- Human Ai Collab: 1 paper
- Skills Training: 1 paper
Claim outcomes
- Organizational Efficiency: 1 paper
- Adoption Rate: 1 paper
- Skill Acquisition: 1 paper
- Wages: 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 |
|---|---|---|---|
| Demand for AI skills in knowledge work has surged since ChatGPT—appearing in 27.8% of job listings and linked to a 17.7% advertised wage premium—while adoption varies from 43.2% in high-tech to 9.7% in the public sector. Conventional appraisal systems miss hybrid human–AI capabilities, so the paper proposes a three-part performance framework (AI Tool Mastery, Collaborative Work Quality, Human–AI Synergy) for firms redesigning work.semantic_scholar | Zhicheng Yu provider id |
Fetched 2026-03-17 | 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.