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
0Unique collaborators
1/1OpenAlex citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5130311614
ORCID evidence
No valid ORCID is stored.
Observed aliases (4)
- Buil Giné, Roman (openalex, provider refresh)
- Buil Giné, Roman (openalex, source metadata)
- Roman Buil Giné (openalex, provider refresh)
- Roman Buil Giné (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Org Design: 1 paper
- Productivity: 1 paper
Claim outcomes
- Other: 1 paper
- Decision Quality: 1 paper
- Firm Productivity: 1 paper
- Organizational Efficiency: 1 paper
- Task Allocation: 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-driven forecasting and optimization system for roadside assistance meaningfully lowered response costs and increased use of internal crews, after backtesting on historical incidents and deployment at scale; the gains are compelling for similar data-rich field services but derive from a single firm rollout without randomized evaluation.openalex | Buil Giné, Roman provider id |
2026-01-27 | 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.