{"id":"W2141985218","doi":"10.3389/fncom.2015.00116","title":"Leg mechanics contribute to establishing swing phase trajectories during memory-guided stepping movements in walking cats: a computational analysis","year":2015,"lang":"en","type":"article","venue":"Frontiers in Computational Neuroscience","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research","keywords":"Swing; Torque; Trajectory; Inverse dynamics; Hindlimb; Knee flexion; Position (finance); Biomechanics; Physics; Computer science; Physical medicine and rehabilitation; Anatomy; Medicine; Acoustics; Classical mechanics; Kinematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001213682,0.0002456209,0.0003456973,0.0003408663,0.0003531247,0.0004462275,0.0004531293,0.0007180178,0.0009080768],"category_scores_gemma":[0.0004955921,0.000348602,0.0004785098,0.000218229,0.0003290636,0.0002581225,0.0002780946,0.0002643772,0.00009712337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004210552,"about_ca_system_score_gemma":0.0008501756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01899059,"about_ca_topic_score_gemma":0.01441588,"domain_scores_codex":[0.999974,0.000004734336,0.00000221076,0.000006709381,0.000006265968,0.000005970122],"domain_scores_gemma":[0.9998122,0.0001020042,0.00002666377,0.00001556614,0.00002149428,0.00002215565],"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":[0.00005178622,0.00005915379,0.007474005,0.00004347902,0.00004281363,0.0002031875,0.00005380423,0.9823674,0.006320723,0.0004420625,0.00005537992,0.002886169],"study_design_scores_gemma":[0.00000538833,0.00001539013,0.001929491,0.000001603828,0.000007818754,0.00001295595,0.000009757461,0.9976608,0.0002377544,0.00008512317,0.00003076704,0.000003175455],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.989069,0.00003871381,0.009892557,0.00005046291,0.000002528401,0.00001821605,0.00008608271,0.00004767355,0.0007947838],"genre_scores_gemma":[0.9967405,0.00004268772,0.002831137,0.000007692842,0.000001716243,0.00002089074,0.0000723872,0.00001106481,0.0002720158],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01899059,"threshold_uncertainty_score":0.03776008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02102776951646555,"score_gpt":0.2643418404448394,"score_spread":0.2433140709283738,"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."}}