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
1/1OpenAlex citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5133832849
ORCID evidence
No valid ORCID is stored.
Observed aliases (2)
- Md Aminul Islam (openalex, provider refresh)
- Md Aminul Islam (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Org Design: 1 paper
- Productivity: 1 paper
Claim outcomes
- Organizational Efficiency: 1 paper
- Other: 1 paper
- Output Quality: 1 paper
- Research Productivity: 1 paper
- Task Completion Time: 1 paper
- Decision Quality: 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 |
|---|---|---|---|
| A synthesis of 142 studies finds AI‑powered business intelligence typically raises efficiency and predictive accuracy—cutting decision latency and improving decision quality—though the evidence largely comes from observational work and may be susceptible to publication and heterogeneity biases.openalex | Md Aminul Islam provider id |
2026-01-01 | 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.