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
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2341913680
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Ramit Debnath (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Governance: 1 paper
- Innovation: 1 paper
Claim outcomes
- Market Structure: 1 paper
- Adoption Rate: 1 paper
- Firm Revenue: 1 paper
- Governance And Regulation: 1 paper
- Other: 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 |
|---|---|---|---|
| London accounts for 41% of Britain’s AI firms, and revenue is driven more by firm size and technical intensity than by local context; nevertheless, regional skills and density provide meaningful boosts. Forecasts to 2030 predict about 4,650 AI entities but a rising dissolution rate, signaling a shift from rapid expansion to consolidation and urging place‑sensitive policy support.arxiv | Ramit Debnath provider id |
2026-02-05 | 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.