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
1/1Semantic Scholar citation coverage
Publication span: 2025. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2304198109
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Matteo Marescotti (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Governance: 1 paper
- Human Ai Collab: 1 paper
- Org Design: 1 paper
- Productivity: 1 paper
Claim outcomes
- Adoption Rate: 1 paper
- Organizational Efficiency: 1 paper
- Regulatory Compliance: 1 paper
- Developer Productivity: 1 paper
- Error Rate: 1 paper
- Governance And Regulation: 1 paper
- Output Quality: 1 paper
- Team Performance: 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 |
|---|---|---|---|
| A bespoke AI developer assistant at WhatsApp tripled automated privacy verification coverage and produced over 3,000 accepted code changes, with 86% bug-triage precision; success hinged as much on ownership, rollout, and risk-management practices as on technical performance.arxiv | Matteo Marescotti provider id |
2025-12-04 | 3 |
Citation observation summary
Semantic Scholar supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 3 cumulative citations. This is a coverage summary, not an author score or h-index.