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
3Unique collaborators
1/1Semantic Scholar citation coverage
Publication dates unavailable. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
3170162
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Kristina McElheran (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Org Design: 1 paper
- Productivity: 1 paper
Claim outcomes
- Adoption Rate: 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 |
|---|---|---|---|
| Fewer than one in four U.S. manufacturing plants reported using AI in 2021, with uptake concentrated among larger, digitally modernized facilities; cost, unclear use cases and skill gaps—not past productivity—appear to limit diffusion.semantic_scholar | Kristina McElheran provider id |
Fetched 2026-05-23 | 1 |
Citation observation summary
Semantic Scholar supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 1 cumulative citations. This is a coverage summary, not an author score or h-index.