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
3Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2040106554
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Samuel Ferino (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Human Ai Collab: 1 paper
- Productivity: 1 paper
- Skills Training: 1 paper
Claim outcomes
- Developer Productivity: 1 paper
- Governance And Regulation: 1 paper
- Research Productivity: 1 paper
- Skill Obsolescence: 1 paper
- Task Allocation: 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 |
|---|---|---|---|
| Interviews with 22 developers show that balancing control over LLMs determines whether these tools boost or erode software work; excessive reliance risks skill atrophy while underuse forfeits productivity gains. The paper offers a preliminary 'reliance–control' framework to guide tool design, training and policy.arxiv | Samuel Ferino provider id |
2026-04-12 | 0 |
Citation observation summary
Semantic Scholar 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.