{"id":"W2088630585","doi":"10.1145/2522628.2522902","title":"Pareto Optimal Control for Natural and Supernatural Motions","year":2013,"lang":"en","type":"article","venue":"","topic":"Human Motion and Animation","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Jump; Optimal control; Pareto optimal; Pareto principle; Motion (physics); Control theory (sociology); Computer science; Motion control; Set (abstract data type); Task (project management); Multi-objective optimization; Span (engineering); Control (management); Mathematical optimization; Mathematics; Physics; Robot; Engineering; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00001787852,0.00004912015,0.00004932664,0.00002210365,0.00003808975,0.00004818833,0.00002344792,0.00002291989,0.0003359184],"category_scores_gemma":[0.000008352774,0.00004079671,0.0000205109,0.00001518157,0.000009135175,0.0001733541,0.000002729274,0.00004302915,0.00005175766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000911582,"about_ca_system_score_gemma":0.000001081649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005340531,"about_ca_topic_score_gemma":0.000006024277,"domain_scores_codex":[0.9997651,0.000002755458,0.00006376933,0.0000501903,0.00002974351,0.00008842463],"domain_scores_gemma":[0.9998889,0.00001316648,0.000003642358,0.00003398004,0.00002725577,0.00003303104],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002733019,0.0001288582,0.006194171,0.0005002578,0.0004531866,0.000002730161,0.002632984,0.04426698,0.3625168,0.2005586,0.2348066,0.1479114],"study_design_scores_gemma":[0.0006367312,0.0000174537,0.0421706,0.000004210383,0.000005855658,0.000003041853,0.00009269864,0.954684,0.0004034937,0.0002394909,0.001641324,0.0001011436],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9380193,0.0001174096,0.0587429,0.0003548765,0.0001992862,0.0002886998,0.000006741318,0.0002717078,0.00199912],"genre_scores_gemma":[0.9969027,0.000004259899,0.002145102,0.00008621083,0.00005918409,0.00003390772,0.00001026524,0.000007549249,0.0007508069],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.910417,"threshold_uncertainty_score":0.3678071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007052219197525795,"score_gpt":0.2022984447464904,"score_spread":0.1952462255489646,"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."}}