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:
A5086694789
ORCID evidence
No valid ORCID is stored.
Observed aliases (4)
- A. Fajri Alvi (openalex, provider refresh)
- A. Fajri Alvi (openalex, source metadata)
- Adeel Alvi (openalex, provider refresh)
- Adeel Alvi (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Productivity: 1 paper
Claim outcomes
- Adoption Rate: 1 paper
- Ai Safety And Ethics: 1 paper
- Decision Quality: 1 paper
- Error Rate: 1 paper
- Other: 1 paper
- Output Quality: 1 paper
- Task Completion Time: 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-enhanced forecasting substantially outperforms traditional models in finance, raising accuracy by about 15 percentage points and cutting processing time by two-thirds across 385 institutions. Firms with stronger organisational readiness, better data and technical infrastructure capture the gains, while privacy, transparency and workforce adaptation remain significant barriers.openalex | Adeel Alvi 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.