{"id":"W2160872810","doi":"10.3389/neuro.12.002.2009","title":"Generating spatiotemporal joint torque patterns from dynamical synchronization of distributed pattern generators","year":2009,"lang":"en","type":"article","venue":"Frontiers in Neurorobotics","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"NeuroDevNet","funders":"Exploratory Research for Advanced Technology","keywords":"Computer science; Synchronization (alternating current); Central pattern generator; Chaotic; Phase synchronization; Robotics; Motor control; Modular design; Control theory (sociology); Robot; Control engineering; Artificial intelligence; Rhythm; Control (management); Neuroscience; Engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000175321,0.00022218,0.0002175621,0.000259241,0.0001459335,0.0002890685,0.0002516953,0.0001961944,0.001323514],"category_scores_gemma":[0.001169993,0.0001918909,0.0002333881,0.0002324012,0.0004482664,0.0003634078,0.0004334267,0.0001938158,0.0001772254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001649877,"about_ca_system_score_gemma":0.0001680867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002687307,"about_ca_topic_score_gemma":0.0002968501,"domain_scores_codex":[0.9999295,0.00001500108,0.000004917025,0.00002073656,0.00002101654,0.000008856564],"domain_scores_gemma":[0.9997656,0.00009372448,0.00005355621,0.00004219279,0.00002206974,0.00002296035],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003244166,0.0001124532,0.00390706,0.0002720261,0.00009118846,0.0009620267,0.000551535,0.1841144,0.6659744,0.03844145,0.0008009768,0.104448],"study_design_scores_gemma":[0.00009270077,0.0001872575,0.009821234,0.00001843831,0.00003089373,0.0004933215,0.0001192205,0.904398,0.0552068,0.02799559,0.00159677,0.0000396669],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6098942,0.0001695661,0.3833695,0.0001509481,0.00004121519,0.00007574555,0.0000900092,0.0002979207,0.005910834],"genre_scores_gemma":[0.9760855,0.00007336257,0.02279067,0.00001350311,0.000009914692,0.00004183806,0.00005933268,0.00002943254,0.0008963827],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001323514,"threshold_uncertainty_score":0.004427612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01686943147363332,"score_gpt":0.2234560190416763,"score_spread":0.206586587568043,"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."}}