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 span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5072907020
ORCID evidence
Observed aliases (2)
- Md Irfanuzzaman Khan (openalex, provider refresh)
- Md Irfanuzzaman Khan (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Human Ai Collab: 1 paper
- Org Design: 1 paper
Claim outcomes
- 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 |
|---|---|---|---|
| Managers trust AI-assisted performance reviews when interactions feel high-quality, allow human oversight and seem human; transparency drives trust most strongly. Firms aiming to increase uptake should prioritise explainability, clear human review and traceable accountability.openalex | Md Irfanuzzaman Khan provider id |
2026-09-09 | 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.