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
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2458255798
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Primzharova Liza (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
Claim outcomes
- Error Rate: 1 paper
- Task Completion Time: 1 paper
- Adoption Rate: 1 paper
- Ai Safety And Ethics: 1 paper
- Employment: 1 paper
- Governance And Regulation: 1 paper
- Organizational Efficiency: 1 paper
- Skill Acquisition: 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 |
|---|---|---|---|
| Audits must move from periodic sampling to embedded, continuous checks: the author proposes an 'Audit as Code' model and an Algorithmic Integrity Protocol to deliver near real-time, machine-readable assurance of financial systems — but the framework remains conceptual and lacks empirical validation.openalex | Primzharova Liza provider id |
2026-08-17 | 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.