{"id":"W6963524536","doi":"10.20380/gi2016.19","title":"PhysIK: Physically Plausible and Intuitive Keyframing","year":2016,"lang":"en","type":"article","venue":"Canada Human-Computer Communications Society","topic":"Human Motion and Animation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Kinematics; Variety (cybernetics); Motion (physics); Inverse kinematics; Degrees of freedom (physics and chemistry); Inertia; Character animation","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":[0.0005105238,0.0009008075,0.0004987749,0.0003295754,0.0004817144,0.001018793,0.001111342,0.001010519,0.01130397],"category_scores_gemma":[0.001929396,0.0004089033,0.0005381007,0.0001440794,0.001030383,0.001590567,0.002369161,0.001019031,0.001989632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002566766,"about_ca_system_score_gemma":0.0002186449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005314674,"about_ca_topic_score_gemma":0.0007000974,"domain_scores_codex":[0.9996682,0.00008567755,0.00001548174,0.00007427004,0.0001192511,0.00003699255],"domain_scores_gemma":[0.9995366,0.0001972049,0.00003156701,0.0001443206,0.00003583315,0.00005447757],"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":[0.0009919098,0.0002831789,0.001952653,0.0008364464,0.0001193704,0.002034211,0.003329897,0.1539804,0.4009515,0.08977767,0.009926593,0.3358161],"study_design_scores_gemma":[0.0001881777,0.0008114678,0.001926954,0.000166751,0.00007509012,0.003327557,0.0005352652,0.7366966,0.09821194,0.04323057,0.1146468,0.0001828145],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04261858,0.0001686196,0.9336087,0.0001788784,0.0001444207,0.0001620659,0.000158482,0.005687566,0.01727267],"genre_scores_gemma":[0.4963175,0.0003121362,0.4873572,0.0001806603,0.00004774176,0.0002681795,0.0005024302,0.001629477,0.0133847],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01130397,"threshold_uncertainty_score":0.03781551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01266419351607596,"score_gpt":0.2063408538114612,"score_spread":0.1936766602953852,"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."}}