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
0Unique collaborators
1/1OpenAlex citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5128336613
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Satyadhar Joshi (openalex, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Governance: 1 paper
- Labor Markets: 1 paper
- Skills Training: 1 paper
Claim outcomes
- Other: 1 paper
- Adoption Rate: 1 paper
- Employment: 1 paper
- Ai Safety And Ethics: 1 paper
- Automation Exposure: 1 paper
- Inequality: 1 paper
- Organizational Efficiency: 1 paper
- Turnover: 1 paper
Papers in the OpenAlex view
Latest stored OpenAlex 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 dynamic, task-based AI exposure architecture would modernize BLS labor projections by mapping LLM-driven capabilities to occupations and combining real-time signals with causal inference to forecast displacement, augmentation, and skill transitions; its success depends on data access, robust LLM validation, and careful backtesting.openalex | Satyadhar Joshi provider id |
2026-03-06 | 0 |
Citation observation summary
OpenAlex 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.