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
3Unique collaborators
1/1OpenAlex citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5138978876
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Akarue Blessing Okiemute Okiemute (openalex, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Productivity: 1 paper
Claim outcomes
- Consumer Welfare: 1 paper
- Adoption Rate: 1 paper
- Innovation Output: 1 paper
- Organizational Efficiency: 1 paper
- Firm Productivity: 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 |
|---|---|---|---|
| Survey evidence from Nigeria suggests AI adoption in agriculture and waste-to-energy is linked to noticeable gains in operational efficiency and environmental sustainability. But infrastructure shortfalls, unstable power, limited technical expertise and high costs remain major obstacles to wider impact.semantic_scholar | Akarue Blessing Okiemute Okiemute provider id |
2026-06-19 | 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.