A multi-dimensional coupling model for detecting science-technology interactions within AI
Bibliographic Data
| ID | 21443036 |
|---|---|
| Authors | Zhichao Ba (0000-0001-5626-5604, Suzhou Research Institute), Leqi Zhu (0009-0001-4342-1898, Suzhou Research Institute, corresponding author), Yujie Zhang (0000-0001-6480-4268, Suzhou Research Institute), Kai Meng (0000-0002-3939-273X, Suzhou Research Institute), Zujun Liu (0000-0002-6638-4225, Digital China Health (China)) |
| Year | 2026 |
| Volume | 131 |
| Issue | 4 |
| Pages | 2731-2767 |
| Publication date | 2026-04-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Scientometrics (JOURNAL) |
| Journal identifiers | ISSN: 0138-9130 • E-ISSN: 1588-2861 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s11192-026-05565-6 |
| OpenAlex | W7128907896 |
| Language | EN |
| References cited | 63 |
Coupling (piping) · Field (mathematics) · Network analysis · Network science · Network topology · Node (physics) · Nonlinear system · Robustness (evolution) · Topology (electrical circuits) · Advanced Graph Neural Networks · Complex Network Analysis Techniques · Computational Drug Discovery Methods
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| Highly cited | No |
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