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: 2025. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2399028457
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Sandeep Neela (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Governance: 1 paper
- Innovation: 1 paper
Claim outcomes
- Other: 1 paper
- Market Structure: 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-driven market-surveillance system that fuses social-coordination signals with price data produces early warning scores—claiming to flag GME 22 days before the January 2021 squeeze—but the public ground-truth release covers only 33 ticker-days (3 positives) and relies on synthetic Reddit features.arxiv | Sandeep Neela provider id |
2025-12-18 | 1 |
Citation observation summary
Semantic Scholar supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 1 cumulative citations. This is a coverage summary, not an author score or h-index.