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
1/1OpenAlex citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5071163664
ORCID evidence
Observed aliases (2)
- Bartłomiej Kizielewicz (openalex, provider refresh)
- Bartłomiej Kizielewicz (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Governance: 1 paper
- Human Ai Collab: 1 paper
Claim outcomes
- Decision Quality: 1 paper
- Ai Safety And Ethics: 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 |
|---|---|---|---|
| Large language models match experts when ranking policy criteria but disagree on scoring and final rankings in Ghana’s renewable-energy MCDA, implying LLMs are valuable for elicitation but need expert oversight and hybrid workflows to produce reliable policy recommendations.openalex | Bartłomiej Kizielewicz provider id |
2026-09-11 | 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.