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:
2268303469
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Feng He (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Governance: 1 paper
- Innovation: 1 paper
- Productivity: 1 paper
Claim outcomes
- Firm Productivity: 1 paper
- Other: 1 paper
- Governance And Regulation: 1 paper
- Hiring: 1 paper
- Innovation Output: 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 |
|---|---|---|---|
| China’s coordinated digital‑intelligent pilot programs raised urban green economic efficiency by roughly 5 percentage points, largely via improved ecological resilience, more green patents and a surge in new firms; effects are strongest in growing/mature resource cities and high‑fintech areas.openalex | Feng He provider id |
2026-02-07 | 2 |
Citation observation summary
Semantic Scholar supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 2 cumulative citations. This is a coverage summary, not an author score or h-index.