{"id":"W2011377734","doi":"10.1016/j.mcm.2009.12.004","title":"Stability criteria for impulsive reaction–diffusion Cohen–Grossberg neural networks with time-varying delays","year":2009,"lang":"en","type":"article","venue":"Mathematical and Computer Modelling","topic":"Neural Networks Stability and Synchronization","field":"Computer Science","cited_by":92,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Program for New Century Excellent Talents in University","keywords":"Reaction–diffusion system; Artificial neural network; Stability (learning theory); Diffusion; Computer science; Applied mathematics; Mathematics; Control theory (sociology); Artificial intelligence; Machine learning; Mathematical analysis; Thermodynamics; Physics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003167727,0.0002384296,0.0003337207,0.00003939278,0.0003563542,0.0003266499,0.0002826087,0.00009532309,0.000008358923],"category_scores_gemma":[0.00000700533,0.0001834624,0.00007529795,0.00019601,0.00006018726,0.0005712754,0.0001185812,0.0001741641,0.000002520965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003506794,"about_ca_system_score_gemma":0.00001423838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002658076,"about_ca_topic_score_gemma":5.634992e-7,"domain_scores_codex":[0.9983712,0.00007529419,0.0003863467,0.0005703913,0.0002053401,0.0003913678],"domain_scores_gemma":[0.9989014,0.0003242818,0.0001022092,0.0003804982,0.0001455465,0.0001460643],"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":[0.0001961051,0.0004696817,0.00003984191,0.0001909596,0.00003114424,0.00001266494,0.001777308,0.8592076,0.0005865042,0.05900133,0.000103475,0.07838341],"study_design_scores_gemma":[0.0003826689,0.0003492797,0.000027261,0.00006464285,0.00001474875,0.00004492895,0.000004819685,0.951179,0.00006861832,0.04762125,0.00001564119,0.0002271662],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1273146,0.00005191586,0.8714204,0.0004848155,0.0000847379,0.000412387,0.000001539923,0.0001652306,0.00006434305],"genre_scores_gemma":[0.7836124,0.000006978824,0.2157916,0.0003432583,0.0001964333,0.00001495787,0.00001056392,0.00001054625,0.0000132775],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6562977,"threshold_uncertainty_score":0.748138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02406176268880843,"score_gpt":0.2372801239728727,"score_spread":0.2132183612840642,"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."}}