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
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2210283785
ORCID evidence
No valid ORCID is stored.
Observed aliases (2)
- D. Leshchikova (semantic scholar, provider refresh)
- Daria Leshchikova (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Human Ai Collab: 1 paper
- Org Design: 1 paper
Claim outcomes
- Adoption Rate: 1 paper
- Decision Quality: 1 paper
- Inequality: 1 paper
- Market Structure: 1 paper
- Organizational Efficiency: 1 paper
- Task Allocation: 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 |
|---|---|---|---|
| Dating-app users are far more willing to delegate messaging to AI than to accept AI-authored messages from others: deployment propensity is about three times higher than engagement propensity, so under random pairing only a small fraction (4–13%) of dyads would have both sides accept agent-mediated conversation; receptivity-aware routing can substantially increase per-contact engagement (AUC 0.88).arxiv | Daria Leshchikova provider id |
2026-08-18 | 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.