{"id":"W1988182159","doi":"10.1145/545261.545275","title":"Modeling tension and relaxation for computer animation","year":2002,"lang":"en","type":"article","venue":"","topic":"Human Motion and Animation","field":"Engineering","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Animation; Computer science; Interactive skeleton-driven simulation; Computer animation; Relaxation (psychology); Computer facial animation; Motion (physics); Motion control; Tension (geology); Skeletal animation; Stiffness; Computer graphics (images); Computer vision; Artificial intelligence; Robot; Compression (physics); Engineering; Structural engineering; 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":[0.00003213386,0.00003355426,0.00003205899,0.00003103961,0.00003486639,0.00002061501,0.000008733417,0.00002296899,0.000053666],"category_scores_gemma":[0.000003379593,0.00003180313,0.000009229158,0.00002002551,0.000001911255,0.0001216207,0.000002283537,0.00001757777,0.00002223089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009435139,"about_ca_system_score_gemma":1.948205e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.902106e-7,"about_ca_topic_score_gemma":0.000001648895,"domain_scores_codex":[0.9998057,0.000002354317,0.00007197388,0.00004711033,0.00002973443,0.00004310165],"domain_scores_gemma":[0.9999273,0.000005809329,0.000005221736,0.0000270435,0.00002030463,0.00001431825],"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":[0.000002205943,0.00001620981,0.00004318702,0.0001146217,0.000008598011,1.491334e-7,0.0008297866,0.8567993,0.01315321,0.01052229,0.008175249,0.1103352],"study_design_scores_gemma":[0.0001350142,0.00001262979,0.0001744881,0.000007560587,0.000001956122,9.508827e-7,0.000009152946,0.9989054,0.00009512171,0.0002026753,0.0004136251,0.0000414602],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.166822,0.00002457248,0.8314878,0.0000612745,0.00004649825,0.0000735455,3.74508e-7,0.0001671304,0.001316743],"genre_scores_gemma":[0.9767898,0.00002304988,0.02292566,0.00004215392,0.00005635087,0.000003932784,0.000007234008,0.000006843166,0.0001449401],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8099678,"threshold_uncertainty_score":0.1296894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03170838860564115,"score_gpt":0.2067074570446369,"score_spread":0.1749990684389958,"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."}}