{"id":"W4252634360","doi":"10.1145/1833351.1781156","title":"Generalized biped walking control","year":2010,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Control theory (sociology); Computer science; Inverted pendulum; Gait; Trajectory; Character (mathematics); Realization (probability); Simulation; Motion (physics); Pendulum; Control (management); Artificial intelligence; Mathematics; Engineering; Physical medicine and rehabilitation","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":[0.0001507477,0.0006789219,0.000481852,0.0002665539,0.0002869922,0.0005952666,0.0006582917,0.0003846551,0.003233139],"category_scores_gemma":[0.0004332067,0.0001704406,0.0003417423,0.0002430787,0.0004348553,0.0003908607,0.0009230825,0.0004162038,0.0005878329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001662371,"about_ca_system_score_gemma":0.0002573186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001813778,"about_ca_topic_score_gemma":0.00181694,"domain_scores_codex":[0.9998363,0.00002770124,0.000009297247,0.00004303499,0.00006408955,0.00001944243],"domain_scores_gemma":[0.9998848,0.00001883776,0.00001362289,0.00003465204,0.00003354455,0.00001458977],"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":[0.0001972231,0.00007466129,0.0004942541,0.0005147626,0.00008374779,0.0004664199,0.0002979696,0.5523722,0.07126374,0.04394938,0.004650994,0.3256346],"study_design_scores_gemma":[0.00004796144,0.0002208331,0.0005728052,0.00003428031,0.00002179784,0.0001321463,0.00002322289,0.9722531,0.0039297,0.01241212,0.01032745,0.00002462201],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03220998,0.0003813904,0.9518037,0.00009471665,0.0001074244,0.00008592509,0.0001142482,0.00199865,0.01320395],"genre_scores_gemma":[0.8640851,0.0004278851,0.1251653,0.0001231913,0.00004925685,0.0002067076,0.0002709395,0.0001506432,0.009521062],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003233139,"threshold_uncertainty_score":0.01081592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008703339972455863,"score_gpt":0.2128347021606122,"score_spread":0.2041313621881563,"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."}}