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
2Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
119115360
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Thomas Jungbauer (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Governance: 1 paper
Claim outcomes
- Consumer Welfare: 1 paper
- Decision Quality: 1 paper
- Task Allocation: 1 paper
- Firm Revenue: 1 paper
- Task Completion Time: 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 |
|---|---|---|---|
| Making platform ranking algorithms transparent can cut both ways: when users understand how prominence maps to fit, platforms can persuade as well as steer, sometimes improving consumer welfare and other times harming it; extending transparency requirements to other recommendation mechanisms can undo any consumer gains.arxiv | Thomas Jungbauer provider id |
2026-08-12 | 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.