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:
A5127669309
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Yifan Ma (openalex, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Governance: 1 paper
- Labor Markets: 1 paper
- Org Design: 1 paper
- Productivity: 1 paper
Claim outcomes
- Firm Productivity: 1 paper
- Adoption Rate: 1 paper
- Ai Safety And Ethics: 1 paper
- Decision Quality: 1 paper
- Error Rate: 1 paper
- Fiscal And Macroeconomic: 1 paper
- Other: 1 paper
- Output Quality: 1 paper
- Regulatory Compliance: 1 paper
- Governance And Regulation: 1 paper
- Market Structure: 1 paper
- Organizational Efficiency: 1 paper
- Skill Acquisition: 1 paper
- Task Completion Time: 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 |
|---|---|---|---|
| Generative AI can sharply raise efficiency and accuracy in corporate finance and tax operations, cutting routine costs and freeing staff for higher‑value work; but realising these gains at scale hinges on addressing data privacy, model reliability, system integration and regulatory accountability.openalex | Yifan Ma provider id |
2026-03-13 | 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.