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
1Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
104055943
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Marco Bornstein (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Governance: 1 paper
- Inequality: 1 paper
- Innovation: 1 paper
Claim outcomes
- Consumer Welfare: 1 paper
- Organizational Efficiency: 1 paper
- Firm Revenue: 1 paper
- Governance And Regulation: 1 paper
- Innovation Output: 1 paper
- Market Structure: 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 cap-and-trade market for AI compute could curb the sector's energy footprint and create room for academics and startups, the authors argue; they claim such a market can be designed to demonstrably cut total computation and monetize efficiency gains.arxiv | Marco Bornstein provider id |
2026-01-27 | 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.