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:
1403595476
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Paul Goldsmith-Pinkham (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Human Ai Collab: 1 paper
- Productivity: 1 paper
Claim outcomes
- Decision Quality: 1 paper
- Organizational Efficiency: 1 paper
- Consumer Welfare: 1 paper
- Other: 1 paper
- Task Completion Time: 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-assisted pulmonary-embolism detection raised radiologist throughput and agreement over time without slowing diagnoses or increasing mortality: agreement with AI-positive flags rose from 70% to 88% over two years while scan volume grew 16% and per-radiologist monthly caseload nearly doubled; clinicians show wide heterogeneity in acceptance rates.arxiv | Paul Goldsmith-Pinkham provider id |
2026-01-19 | 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.