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: 2025. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5121727186
ORCID evidence
No valid ORCID is stored.
Observed aliases (4)
- Indonesia Universitas Bengkulu (openalex, provider refresh)
- Indonesia Universitas Bengkulu (openalex, source metadata)
- Universitas Bengkulu, Indonesia (openalex, provider refresh)
- Universitas Bengkulu, Indonesia (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Governance: 1 paper
- Human Ai Collab: 1 paper
Claim outcomes
- Organizational Efficiency: 1 paper
- Worker Satisfaction: 1 paper
- Decision Quality: 1 paper
- Governance And Regulation: 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 recommendations in Bengkulu’s provincial budgeting are linked to less budget padding and higher employee motivation, suggesting algorithmic advice can both tighten fiscal oversight and boost engagement; however, evidence derives from a single cross‑sectional survey and cannot firmly establish causality.openalex | Universitas Bengkulu, Indonesia provider id |
2025-12-31 | 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.