{"id":"W2765182962","doi":"10.3934/dcds.2018039","title":"Propagation phenomena for CNNs with asymmetric templates and distributed delays","year":2017,"lang":"en","type":"article","venue":"Discrete and Continuous Dynamical Systems","topic":"Neural Networks Stability and Synchronization","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Monotone polygon; Template; Cellular neural network; Function (biology); Wave speed; Traveling wave; Topology (electrical circuits); Mathematics; Pure mathematics; Computer science; Physics; Combinatorics; Mathematical analysis; Artificial neural network; Geometry; Artificial intelligence","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":[0.0002072542,0.0001391905,0.000239797,0.00003465134,0.000573158,0.0008811306,0.0002748117,0.00006579164,1.862873e-7],"category_scores_gemma":[0.00006129596,0.00009832962,0.00002497731,0.00009524808,0.000112307,0.0005112989,0.0001124972,0.00006860498,3.592151e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000263939,"about_ca_system_score_gemma":0.00001310605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009872924,"about_ca_topic_score_gemma":0.0000524203,"domain_scores_codex":[0.9989909,0.00004551368,0.0002076915,0.0003831057,0.000135632,0.0002371658],"domain_scores_gemma":[0.999157,0.0001049454,0.0001806996,0.0003578851,0.00009921687,0.0001003232],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000275424,0.0001711606,0.07239545,0.0008329212,0.0002125742,0.00002766881,0.0008128943,0.001070529,0.0007844655,0.7294203,0.0001778855,0.1938187],"study_design_scores_gemma":[0.0006680745,0.0003202781,0.01019408,0.00006568932,0.00001901304,0.00002477418,0.00006377262,0.987397,0.00001797609,0.0007422707,0.0002889063,0.0001982043],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1291996,0.0002550489,0.8689517,0.0004632598,0.0001172477,0.0006662864,0.00004020799,0.00006297476,0.0002437327],"genre_scores_gemma":[0.9991937,0.0000131749,0.0005069283,0.00001377005,0.00007678765,0.00007008349,0.00005062505,0.000008262777,0.00006672472],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9863265,"threshold_uncertainty_score":0.8496763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009109492543712142,"score_gpt":0.2240974071532729,"score_spread":0.2149879146095607,"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."}}