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
5Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2373882628
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Ebimoboere Koroye (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Human Ai Collab: 1 paper
- Innovation: 1 paper
- Productivity: 1 paper
- Skills Training: 1 paper
Claim outcomes
- Governance And Regulation: 1 paper
- Organizational Efficiency: 1 paper
- Skill Acquisition: 1 paper
- Adoption Rate: 1 paper
- Market Structure: 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 |
|---|---|---|---|
| AI-powered mobile money systems are improving transactional efficiency for Nigerian SMEs—boosting logistics knowledge, increasing trust and reducing supply-chain fraud—and their diffusion is reshaping local economic forces in cities such as Lagos and Abuja.openalex | Ebimoboere Koroye provider id |
2026-01-16 | 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.