{"id":"W2056316267","doi":"10.1145/545261.545286","title":"EigenSkin","year":2002,"lang":"en","type":"article","venue":"","topic":"Human Motion and Animation","field":"Engineering","cited_by":270,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Skinning; Computer science; Subspace topology; Graphics hardware; Nonlinear system; Rendering (computer graphics); Animation; Computer graphics (images); Character animation; Graphics; Vertex (graph theory); Artificial intelligence; Computation; Algorithm; Construct (python library); Computer vision; Computer animation; Theoretical computer science; Graph; Engineering","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":[0.0001889974,0.0006050483,0.0005376993,0.0004656275,0.0003991393,0.0007933767,0.0008808643,0.000340027,0.01027326],"category_scores_gemma":[0.0007479314,0.000454209,0.000554677,0.0003950546,0.0004552781,0.001215055,0.001396465,0.0007470456,0.00325737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002665282,"about_ca_system_score_gemma":0.000502839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001037338,"about_ca_topic_score_gemma":0.002142608,"domain_scores_codex":[0.9997669,0.00002053654,0.00001323215,0.00004898084,0.0001301639,0.00002028304],"domain_scores_gemma":[0.9997645,0.00003708471,0.00001789572,0.0001222951,0.00003836802,0.00001983646],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003084606,0.0001235323,0.001358054,0.0002354151,0.00005614822,0.0004469473,0.0004415128,0.1867469,0.184468,0.1260706,0.01126367,0.4884807],"study_design_scores_gemma":[0.00002573491,0.00009320997,0.0006732831,0.0000245278,0.00001475119,0.0004722821,0.00007175394,0.8474815,0.06727076,0.03378061,0.05004465,0.0000469417],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01450061,0.00006810558,0.976072,0.00004768695,0.00006493228,0.00003206775,0.0001593856,0.002575373,0.006479857],"genre_scores_gemma":[0.2943684,0.0002874483,0.6783895,0.00009743778,0.00003989126,0.0001574988,0.00101946,0.001802303,0.02383811],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01027326,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01766634640189086,"score_gpt":0.158952983918506,"score_spread":0.1412866375166151,"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."}}