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: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5147367318
ORCID evidence
No valid ORCID is stored.
Observed aliases (2)
- Ming-Chia Chen (openalex, provider refresh)
- Ming-Chia Chen (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Human Ai Collab: 1 paper
- Innovation: 1 paper
- Org Design: 1 paper
Claim outcomes
- Innovation Output: 1 paper
- Organizational Efficiency: 1 paper
- Governance And Regulation: 1 paper
- Skill Acquisition: 1 paper
- Team Performance: 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 partnerships with industry reshape universities’ knowledge assets and boost innovation — structural, not just human, capital does the heavy lifting; governance arrangements matter more than raw adoption levels.openalex | Ming-Chia Chen provider id |
2026-08-11 | 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.