{"id":"W2018571963","doi":"10.1145/1778765.1781156","title":"Generalized biped walking control","year":2010,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Human Motion and Animation","field":"Engineering","cited_by":219,"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); Motion control; Control (management); Artificial intelligence; Mathematics; Robot; 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":[0.0001527718,0.0006703211,0.0004827738,0.0002667226,0.0002803988,0.0005991446,0.0006605032,0.0003878115,0.003317631],"category_scores_gemma":[0.0004439686,0.0001717439,0.0003396214,0.0002420029,0.0004306653,0.0003899355,0.0009244692,0.0004122439,0.0005949901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001644749,"about_ca_system_score_gemma":0.0002564882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001811231,"about_ca_topic_score_gemma":0.001783051,"domain_scores_codex":[0.999838,0.00002753813,0.000009132221,0.00004274783,0.00006347433,0.0000189856],"domain_scores_gemma":[0.9998862,0.00001899834,0.000013374,0.00003406398,0.00003267829,0.00001472474],"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":[0.000202157,0.00007425012,0.0004916532,0.0005101801,0.00008491008,0.0004577062,0.0002953749,0.5583845,0.07268391,0.0433755,0.004581617,0.3188582],"study_design_scores_gemma":[0.00004955887,0.0002178852,0.0005666146,0.00003359703,0.00002216659,0.0001289182,0.00002254142,0.9729436,0.003920942,0.01174548,0.01032433,0.00002441022],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03287816,0.0003870356,0.9510644,0.00009731901,0.0001106789,0.00008861242,0.0001143142,0.002038586,0.01322087],"genre_scores_gemma":[0.8647937,0.0004342067,0.1243635,0.0001221948,0.00005084751,0.0002064602,0.0002656745,0.000152486,0.009610898],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003317631,"threshold_uncertainty_score":0.01109856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01193321255692081,"score_gpt":0.2246672913070914,"score_spread":0.2127340787501706,"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."}}