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
36Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2449782053
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Toby Clowes (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Governance: 1 paper
- Innovation: 1 paper
- Org Design: 1 paper
Claim outcomes
- Market Structure: 1 paper
- Adoption Rate: 1 paper
- Governance And Regulation: 1 paper
- Ai Safety And Ethics: 1 paper
- Firm Revenue: 1 paper
- Innovation Output: 1 paper
- Organizational Efficiency: 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 |
|---|---|---|---|
| Insurance can unlock a multi‑trillion dollar AI agent economy, but current silent coverage and rising correlated risks mean coverage must be redesigned; industry-wide standards, pooled instruments and government backstops are needed to enable billion-dollar affirmative policies and manage catastrophic AI scenarios.openalex | Toby Clowes provider id |
2026-07-13 | 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.