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 →
2Distinct papers
3Unique collaborators
2/2Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
88738815
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Ashesh Rambachan (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Innovation: 2 papers
- Adoption: 1 paper
- Human Ai Collab: 1 paper
Claim outcomes
- Research Productivity: 2 papers
- Output Quality: 2 papers
- Error Rate: 2 papers
- Decision Quality: 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 |
|---|---|---|---|
| AI turns measurement from a bottleneck into a choice problem: economists can cheaply generate many plausible variables from text and images, but reliable inference now depends on explicit construct definitions and careful validation (ideally randomized or well-designed validation samples).arxiv | Ashesh Rambachan provider id |
2026-08-24 | 0 |
| Large language models can unlock large-scale text-based economic research, but only if researchers guard against training-data leakage for prediction and use an independent validation sample to correct LLM measurement errors or risk biased and imprecise estimates.openalex | Ashesh Rambachan provider id |
2026-04-06 | 63 |
Citation observation summary
Semantic Scholar supplied counts for 2 of 2 papers in this view; 0 are missing. The observed paper counts sum to 63 cumulative citations. This is a coverage summary, not an author score or h-index.