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
1Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2455115727
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Fanzhe Wei (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Governance: 1 paper
- Productivity: 1 paper
Claim outcomes
- Output Quality: 1 paper
- Task Allocation: 1 paper
- Automation Exposure: 1 paper
- Organizational Efficiency: 1 paper
- Regulatory Compliance: 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 |
|---|---|---|---|
| A machine-checked 'anytime' risk ledger halved exact-fallbacks in live model serving while preserving per-request guarantees, turning runtime compression risk into an auditable, spendable account; the remaining gap to observed errors is localized to the gate operating point, enabling explicit pricing of quality–capacity trade-offs.arxiv | Fanzhe Wei provider id |
2026-08-16 | 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.