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
6Unique collaborators
1/1OpenAlex citation coverage
Publication dates unavailable. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5008757494
ORCID evidence
Observed aliases (2)
- Heather F. Neyedli (openalex, provider refresh)
- Heather Neyedli (openalex, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Human Ai Collab: 1 paper
- Productivity: 1 paper
- Skills Training: 1 paper
Claim outcomes
- Ai Safety And Ethics: 1 paper
- Adoption Rate: 1 paper
- Decision Quality: 1 paper
- Error Rate: 1 paper
- Firm Productivity: 1 paper
- Output Quality: 1 paper
- Skill Acquisition: 1 paper
- Task Allocation: 1 paper
- Task Completion Time: 1 paper
- Team Performance: 1 paper
- Worker Satisfaction: 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 |
|---|---|---|---|
| Human–AI co-learning with a metacognitive 'Cognitive Shadow' speeds decisions and reduces missed detections in simulated Arctic surveillance, while confidence estimates enable safe adjustable autonomy. The approach promises productivity gains and easier procurement adoption but remains to be validated in real-world operations.semantic_scholar | Heather Neyedli orcid |
Fetched 2026-03-18 | 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.