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
7Unique collaborators
1/1OpenAlex citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5123384634
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Shunnan Zhao (openalex, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Human Ai Collab: 1 paper
- Org Design: 1 paper
- Productivity: 1 paper
Claim outcomes
- Organizational Efficiency: 1 paper
- Decision Quality: 1 paper
- Adoption Rate: 1 paper
- Error Rate: 1 paper
- Firm Productivity: 1 paper
- Innovation Output: 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 |
|---|---|---|---|
| An AI assistant that combines OCR with LLMs slashed petroleum engineering design time by about 75% and eliminated over 95% of clerical errors in a >1,000-well deployment, enabling large operators to standardize designs and mine decades of legacy ‘dark’ data — though the evaluation lacks independent controls.semantic_scholar | Shunnan Zhao provider id |
2026-06-16 | 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.