{"id":"W1974666882","doi":"10.1115/1.4005462","title":"Foot Placement and Balance in 3D","year":2012,"lang":"en","type":"article","venue":"Journal of Computational and Nonlinear Dynamics","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Pendulum; Dynamic balance; Inverted pendulum; Balance (ability); Gait; Estimator; Control theory (sociology); Work (physics); Multibody system; Computer science; Mathematics; Physical medicine and rehabilitation; Engineering; Physics; Classical mechanics; Nonlinear system; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001921771,0.0004684089,0.0003802349,0.0009713294,0.0002145248,0.001099658,0.0002757031,0.0007047316,0.001297392],"category_scores_gemma":[0.001411341,0.0003671436,0.000365719,0.0005434065,0.0004943053,0.0005906907,0.0007804389,0.0002241316,0.0004151709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002269148,"about_ca_system_score_gemma":0.000300918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005334824,"about_ca_topic_score_gemma":0.004828945,"domain_scores_codex":[0.9998465,0.00003442929,0.000008379077,0.00003931911,0.00005876448,0.00001271961],"domain_scores_gemma":[0.9997833,0.00007188652,0.0000594431,0.00002508549,0.00004793696,0.00001235398],"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":[0.0004465697,0.00009793715,0.02616794,0.000194448,0.0001510903,0.0006784403,0.0004557057,0.7162517,0.06615292,0.009080409,0.001642759,0.1786801],"study_design_scores_gemma":[0.00002564379,0.000104039,0.02417232,0.00002947717,0.0000277134,0.0002897077,0.0001569511,0.9606877,0.005145418,0.00717269,0.002136156,0.00005212399],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2846643,0.0004814325,0.7088837,0.0002024624,0.00006384988,0.00004623226,0.0006406285,0.0008330571,0.004184308],"genre_scores_gemma":[0.9526892,0.0003037852,0.0458056,0.00004558197,0.00001794733,0.00003262005,0.0002536229,0.00003364894,0.0008178905],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005334824,"threshold_uncertainty_score":0.01060754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005365616384275658,"score_gpt":0.2137661792939268,"score_spread":0.2084005629096511,"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."}}