{"id":"W4229890538","doi":"10.1145/1399504.1360682","title":"Musculotendon simulation for hand animation","year":2008,"lang":"en","type":"article","venue":"","topic":"Human Motion and Animation","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Animation; Computer science; Pipeline (software); Interactive skeleton-driven simulation; Computer animation; Computer facial animation; Computer graphics (images); Character animation; Skeletal animation; Character (mathematics); Track (disk drive); Motion (physics); Simulation; Computer vision","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":[0.00002802116,0.00003884741,0.00003673493,0.00003510414,0.00007733822,0.00001228481,0.00001535072,0.00002305449,0.0001260527],"category_scores_gemma":[0.00001176979,0.00003776791,0.00002370767,0.00003426699,0.000006727581,0.0001264875,0.000001292993,0.00001576726,0.00005741346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001622276,"about_ca_system_score_gemma":0.000001821816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.397467e-7,"about_ca_topic_score_gemma":0.000002885369,"domain_scores_codex":[0.999772,0.000002687631,0.00008248782,0.00004308733,0.0000432892,0.00005645555],"domain_scores_gemma":[0.999894,0.00001789686,0.000007695177,0.00003763715,0.00002618059,0.00001658603],"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":[0.00001023513,0.0000178504,0.0001119218,0.00007151291,0.00001101746,3.906437e-7,0.0007903001,0.9489497,0.03110689,0.003876323,0.003855376,0.01119848],"study_design_scores_gemma":[0.0004226285,0.00001563743,0.007401695,0.000002848839,0.000002023638,9.07228e-7,0.000009522589,0.9798067,0.003056161,0.0001488821,0.009076856,0.00005610264],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3050588,0.00001035446,0.6878707,0.00001702074,0.00006518433,0.000142936,0.000001251941,0.0002343518,0.006599397],"genre_scores_gemma":[0.9969109,0.000005238688,0.002320838,0.00002071987,0.00006294263,0.00001150329,0.00002335845,0.000009140453,0.0006353823],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6918521,"threshold_uncertainty_score":0.1540131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03406527993012591,"score_gpt":0.2467242849652258,"score_spread":0.2126590050350999,"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."}}