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
1/1OpenAlex citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5144211292
ORCID evidence
No valid ORCID is stored.
Observed aliases (2)
- NianZhu Qiu (openalex, provider refresh)
- NianZhu Qiu (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Governance: 1 paper
- Inequality: 1 paper
- Innovation: 1 paper
Claim outcomes
- Governance And Regulation: 1 paper
- Ai Safety And Ethics: 1 paper
- Inequality: 1 paper
- Market Structure: 1 paper
- Organizational Efficiency: 1 paper
- Regulatory Compliance: 1 paper
Papers in the OpenAlex view
Latest stored OpenAlex 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 |
|---|---|---|---|
| To secure both national interests and AI development, China should adopt a tiered regulatory regime for cross‑border generative AI training data; drawing on EU rights‑focused and U.S. market/security approaches, the paper recommends differentiated data preconditions, an independent regulator with multilevel coordination, and international articulation of China's data governance.openalex | NianZhu Qiu provider id |
2026-08-01 | 0 |
Citation observation summary
OpenAlex 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.