{"id":"W4366189221","doi":"10.1017/s0263574723000413","title":"Gait optimization and energy-based stability for biped locomotion using large-scale programming","year":2023,"lang":"en","type":"article","venue":"Robotica","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Dalhousie University","funders":"","keywords":"Control theory (sociology); Gait; Stability (learning theory); Kinematics; Computer science; Curse of dimensionality; Effect of gait parameters on energetic cost; Optimization problem; Gait analysis; Artificial intelligence; Control (management); Algorithm; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002388396,0.0001289363,0.0001623952,0.00009724886,0.0001227815,0.00006144815,0.00005375268,0.00008793796,0.00002979237],"category_scores_gemma":[0.00002742523,0.0001351488,0.00005672402,0.0002889942,0.00002356893,0.00009660286,0.00001474765,0.000058423,0.00000388838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000571444,"about_ca_system_score_gemma":0.00001988706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004975633,"about_ca_topic_score_gemma":0.00001420709,"domain_scores_codex":[0.9991516,0.00003185115,0.0002021056,0.0001945582,0.0001110758,0.0003087369],"domain_scores_gemma":[0.9995916,0.00007331427,0.00002647533,0.0001606384,0.00006102576,0.00008698047],"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":[0.000006650366,0.00003210237,0.0002167905,0.000101138,0.00001295543,6.063067e-7,0.00006813684,0.9931762,0.0009790653,0.0004605119,0.00004105626,0.00490475],"study_design_scores_gemma":[0.0008018999,0.00003550648,0.0001461148,0.00002547779,0.00003179659,8.454539e-7,0.00006175393,0.9975929,0.0005690753,0.00008515888,0.0005043491,0.0001451652],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004221955,0.00003728607,0.9943767,0.0001997114,0.0001671858,0.0002737497,0.000007953567,0.0006320923,0.00008340654],"genre_scores_gemma":[0.8619717,0.00001106809,0.1375924,0.00005066017,0.00008641271,0.00009181719,0.00009388076,0.00004978101,0.00005223111],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8577498,"threshold_uncertainty_score":0.5511209,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01989924596933063,"score_gpt":0.2329289501186632,"score_spread":0.2130297041493326,"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."}}