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: 2025. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2401557794
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Dmytro Filatov (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Human Ai Collab: 1 paper
- Productivity: 1 paper
Claim outcomes
- Other: 1 paper
- Organizational Efficiency: 1 paper
- Task Completion Time: 1 paper
- Ai Safety And Ethics: 1 paper
- Hiring: 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 |
|---|---|---|---|
| An AI multi-agent hiring assistant halved screening time for a mid-level Python backend role—cutting time per qualified candidate from 3.33 to 1.70 hours—while producing similar precision/recall to an experienced recruiter; the result is promising but based on a single-role, 64-applicant test and may not generalize. arxiv | Dmytro Filatov provider id |
2025-12-17 | 2 |
Citation observation summary
Semantic Scholar supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 2 cumulative citations. This is a coverage summary, not an author score or h-index.