{"id":"W4396650127","doi":"10.1016/j.automatica.2024.111695","title":"Learning nonlinear dynamics in synchronization of knowledge-based leader-following networks","year":2024,"lang":"en","type":"article","venue":"Automatica","topic":"Neural Networks Stability and Synchronization","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"Basic and Applied Basic Research Foundation of Guangdong Province; Natural Sciences and Engineering Research Council of Canada; Science, Technology and Innovation Commission of Shenzhen Municipality","keywords":"Synchronization (alternating current); Dynamics (music); Nonlinear system; Computer science; Control theory (sociology); Artificial intelligence; Control (management); Physics; Computer network","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004495902,0.0001267386,0.0002028328,0.0001726218,0.000069927,0.0001252613,0.0003200321,0.0000988535,0.00001004374],"category_scores_gemma":[0.0001072781,0.0001250363,0.00008459874,0.001375293,0.00004098447,0.0004014689,0.00008399544,0.0002465202,0.00001954184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002394807,"about_ca_system_score_gemma":0.0001557518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001145938,"about_ca_topic_score_gemma":0.00007843255,"domain_scores_codex":[0.998713,0.0001661522,0.0003962808,0.000303372,0.0001769741,0.0002442249],"domain_scores_gemma":[0.9991697,0.0004226623,0.00005670317,0.0002651146,0.00004555019,0.00004028251],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002746432,0.0001391719,0.0055538,0.0004716767,0.00002406604,0.00003179986,0.001163487,0.7774155,0.00004187961,0.03342296,0.00005419168,0.1816787],"study_design_scores_gemma":[0.0001364175,0.00006856504,0.0004959889,0.0003905709,0.00000843372,0.000001946452,0.00003649412,0.9981793,0.00007382668,0.0003793971,0.0001066162,0.0001224072],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0320789,0.0005888009,0.9649204,0.0004727467,0.0004974428,0.0001687781,4.356046e-7,0.0004347011,0.0008378035],"genre_scores_gemma":[0.98392,0.00000980378,0.01587939,0.00002853841,0.00005370359,0.000008301485,0.00002372278,0.000015767,0.00006072969],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9518411,"threshold_uncertainty_score":0.5098832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009116314538915461,"score_gpt":0.2476773705299725,"score_spread":0.238561055991057,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}