{"id":"W1512099791","doi":"10.1115/1.4031086","title":"A Neuronal Model of Central Pattern Generator to Account for Natural Motion Variation","year":2015,"lang":"en","type":"article","venue":"Journal of Computational and Nonlinear Dynamics","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Central pattern generator; Digital pattern generator; Generator (circuit theory); Computer science; Motion (physics); Control theory (sociology); Population; Vibration; CpG site; Biological system; Physics; Artificial intelligence; Control (management); Acoustics; Rhythm; Biology; Power (physics)","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":[0.00009352781,0.00006414782,0.0001157693,0.0001065156,0.00002207517,0.00001446089,0.00003901454,0.00002168991,4.188748e-7],"category_scores_gemma":[0.00002429681,0.00005782302,0.00004676855,0.00007777008,0.000008559025,0.0001155328,0.000007606768,0.00006564155,5.545962e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004845339,"about_ca_system_score_gemma":0.00003848384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001461311,"about_ca_topic_score_gemma":0.000005123725,"domain_scores_codex":[0.9994624,0.00000736474,0.0002342954,0.00004527908,0.0001690659,0.0000815584],"domain_scores_gemma":[0.9994287,0.00003759335,0.0000827633,0.0000208224,0.0003681087,0.00006201717],"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":[0.00004157881,0.00002582388,0.0003954316,0.00002099291,0.00004740079,1.609648e-7,0.0002364476,0.9802866,0.0004432947,0.0002866713,0.0001703664,0.01804522],"study_design_scores_gemma":[0.00044019,0.00008634407,0.02188486,0.000008345368,0.00001364421,0.000006024816,0.00002253119,0.9758838,0.00007271258,0.001481655,0.00004581255,0.00005412842],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5043025,0.00002889048,0.495257,0.0001924998,0.0001443174,0.00003999009,0.000025039,0.000005116658,0.000004617126],"genre_scores_gemma":[0.9593269,0.000009956368,0.04036501,0.0000960512,0.0001643942,0.000001286836,0.00002523179,0.000007877617,0.000003253546],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4550245,"threshold_uncertainty_score":0.2357954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01443273549718825,"score_gpt":0.2291743249893803,"score_spread":0.214741589492192,"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."}}