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
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2307029545
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Tianchi Lu (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Governance: 1 paper
- Human Ai Collab: 1 paper
- Innovation: 1 paper
- Org Design: 1 paper
Claim outcomes
- Organizational Efficiency: 1 paper
- Innovation Output: 1 paper
- Decision Quality: 1 paper
- Other: 1 paper
Papers in the Semantic Scholar view
Latest stored Semantic Scholar 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 new theory argues firms gain AI-driven advantage through a recursive human–machine 'cognitive flywheel', formalized with coupled non-linear dynamics; it recommends fractal governance to reduce automation bias but offers no empirical validation.openalex | Tianchi Lu provider id |
2026-03-15 | 0 |
Citation observation summary
Semantic Scholar 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.