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
8Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2324054022
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Guancheng Wan (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Innovation: 1 paper
Claim outcomes
- Other: 1 paper
- Decision Quality: 1 paper
- Adoption Rate: 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 |
|---|---|---|---|
| LLM traders mimic some—but not all—behavioral-finance patterns in simulated markets; prompted agents switch strategies in theoretically expected directions only intermittently, implying current LLM-based simulations are informative but not yet reliable proxies for real traders.arxiv | Guancheng Wan provider id |
2026-02-02 | 4 |
Citation observation summary
Semantic Scholar supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 4 cumulative citations. This is a coverage summary, not an author score or h-index.