Limited knowledge exchange across biological subfields in agent-based modelling
A bibliometric analysis of 22,936 agent-based modelling articles from Web of Science, classified by an LLM into biological subfields. Based on citations and author overlap, 83%, 81% and 69% of references in ecology, epidemiology and oncology stay within their own subfield.
Why it matters
Shows modelling methods transfer poorly between domains, limiting reuse of approaches in large systems.
Relevant to DT products
- Original headline
- Limited knowledge exchange across biological subfields in agent-based modelling: an LLM-assisted bibliometric analysis
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