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 dates unavailable. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5091411188
ORCID evidence
No valid ORCID is stored.
Observed aliases (2)
- Vijay Baban Jadhav (openalex, provider refresh)
- Vijay Jadhav (openalex, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Labor Markets: 1 paper
- Productivity: 1 paper
Claim outcomes
- Adoption Rate: 1 paper
- Fiscal And Macroeconomic: 1 paper
- Developer Productivity: 1 paper
- Governance And Regulation: 1 paper
- Labor Share: 1 paper
- Market Structure: 1 paper
- Other: 1 paper
- Skill Acquisition: 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 conservative, sector-level model finds AI could add around $1.06 trillion a year to US GDP by 2036 (3.6% of 2024 GDP), mostly driven by services and finance; even under bearish assumptions direct productivity gains approach $800–940 billion and infrastructure payback occurs before 2036.semantic_scholar | Vijay Jadhav provider id |
Fetched 2026-04-14 | 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.