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
5Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2303655574
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Dariia Karaeva (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Human Ai Collab: 1 paper
- Productivity: 1 paper
Claim outcomes
- Other: 1 paper
- Task Completion Time: 1 paper
- Developer Productivity: 1 paper
- Organizational Efficiency: 1 paper
- Adoption Rate: 1 paper
- Output Quality: 1 paper
Papers in the Semantic Scholar view
Latest stored Semantic Scholar 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 |
|---|---|---|---|
| Developers with AI coding assistants write substantially more — but also delete more — indicating faster iteration rather than straightforwardly higher-quality output; users report productivity gains but few perceived changes in other workflow areas.arxiv | Dariia Karaeva provider id |
2026-01-15 | 2 |
Citation observation summary
Semantic Scholar supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 2 cumulative citations. This is a coverage summary, not an author score or h-index.