LightGBM models on citation and diversity features predict exogenous diffusion of quantum computing concepts with R² up to 0.78 while endogenous reinforcement remains largely unpredictable after growth controls, with replications in other fields.
Large teams develop and small teams disrupt science and technology
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A two-stage LightGBM model on 59 features from concept networks forecasts link formation and intensity with ROC-AUC 0.95-0.967 across domains.
A 69.8M-edge cross-corpus graph shows science influencing software mainly via reproducibility and sequence tools while software influences science via ML infrastructure, but direct links are sparse and reuse-citation correlations flip sign depending on the pairing method.
The paper proposes a four-role framework for LLMs in scientific innovation and reviews methods, benchmarks, and limitations across Assistant, Collaborator, Scientist, and Evaluator roles.
citing papers explorer
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Forecasting Conceptual Diffusion in Science: The Case of Quantum Computing
LightGBM models on citation and diversity features predict exogenous diffusion of quantum computing concepts with R² up to 0.78 while endogenous reinforcement remains largely unpredictable after growth controls, with replications in other fields.
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Explainable Forecasting of Scientific Breakthroughs from Concept Network Dynamics
A two-stage LightGBM model on 59 features from concept networks forecasts link formation and intensity with ROC-AUC 0.95-0.967 across domains.
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The Reciprocal Impact of Science and Software: A Cross-Corpus Analysis of How Research Shapes Software and Software Enables Research
A 69.8M-edge cross-corpus graph shows science influencing software mainly via reproducibility and sequence tools while software influences science via ML infrastructure, but direct links are sparse and reuse-citation correlations flip sign depending on the pairing method.
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Evolving Roles of LLMs in Scientific Innovation: Assistant, Collaborator, Scientist, and Evaluator
The paper proposes a four-role framework for LLMs in scientific innovation and reviews methods, benchmarks, and limitations across Assistant, Collaborator, Scientist, and Evaluator roles.