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:
2425090249
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Norainee Mohamed (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Governance: 1 paper
- Innovation: 1 paper
- Productivity: 1 paper
- Skills Training: 1 paper
Claim outcomes
- Fiscal And Macroeconomic: 1 paper
- Adoption Rate: 1 paper
- Inequality: 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 |
|---|---|---|---|
| A Regional AI Hub could push Johor’s GDP to RM260 billion by 2030, with AI responsible for about RM41.5 billion of the projected growth, but systemic SME constraints in finance, governance and skills risk blunting the plan’s impact.openalex | Norainee Mohamed provider id |
2026-01-01 | 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.