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
0/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2275117
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Sudheer Chava (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Innovation: 1 paper
Claim outcomes
- Decision Quality: 1 paper
- Ai Safety And Ethics: 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 |
|---|---|---|---|
| Web-enabled LLMs can nowcast the economy in real time: in a six-month live test across 16 U.S. indicators the best LLM (GPT‑5) matched the Bloomberg economist consensus on a market-weighted accuracy metric, while several models were competitive with Fed nowcasts on GDP and unemployment; however, accuracy varies widely across series and results depend on live web access and a limited evaluation window.arxiv | Sudheer Chava provider id |
2026-08-31 | Missing, not zero |
Citation observation summary
Semantic Scholar supplied counts for 0 of 1 papers in this view; 1 are missing.