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
1/1Semantic Scholar citation coverage
Publication dates unavailable. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2409180322
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Fatma Cherif (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Governance: 1 paper
- Productivity: 1 paper
- Skills Training: 1 paper
Claim outcomes
- Firm Productivity: 1 paper
- Firm Revenue: 1 paper
- Research Productivity: 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 adoption raises Tunisian SMEs' financial and operational performance, but the returns concentrate in firms with stronger finance and technical skills; weak formal institutions do not significantly blunt these gains, implying firms use adaptive informal mechanisms.semantic_scholar | Fatma Cherif provider id |
Fetched 2026-03-15 | 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.