{"id":"W3048496284","doi":"10.1145/3386569.3392379","title":"RigNet","year":2020,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":119,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Animation; Character (mathematics); Skeleton (computer programming); Representation (politics); Character animation; Computer graphics (images); Polygon mesh; Surface (topology); Computer animation; 3d model; Skinning; Architecture; Artificial intelligence; Algorithm; Topology (electrical circuits); Computer vision; Mathematics; Geometry; Programming language","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008425328,0.002428854,0.001206259,0.001527616,0.0007263764,0.002508914,0.003427665,0.002215777,0.04903726],"category_scores_gemma":[0.003762027,0.0009810069,0.001534824,0.0008752458,0.0007418412,0.002124692,0.002891372,0.001970607,0.02019432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00106278,"about_ca_system_score_gemma":0.001090282,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006030271,"about_ca_topic_score_gemma":0.01664303,"domain_scores_codex":[0.99927,0.0001087424,0.00003090944,0.0002295546,0.0002806967,0.00008012629],"domain_scores_gemma":[0.9994659,0.0001399686,0.00002623047,0.0002018341,0.0001132683,0.00005277936],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006599565,0.0002478328,0.001782333,0.0009489047,0.0002587218,0.0006207084,0.0002810867,0.1198701,0.01544648,0.03007154,0.2329053,0.596907],"study_design_scores_gemma":[0.00009286644,0.0001745098,0.0004955927,0.0001441924,0.00003563619,0.0004088917,0.00009093885,0.8371819,0.00981095,0.03277552,0.1187353,0.0000537273],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01118955,0.001110912,0.792234,0.0005450718,0.0008226305,0.0006186205,0.0090449,0.1447381,0.03969616],"genre_scores_gemma":[0.1430378,0.001076405,0.7537388,0.00116506,0.0001794489,0.0009994928,0.0449288,0.01335678,0.04151745],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04903726,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0258789781148894,"score_gpt":0.2127141300871455,"score_spread":0.1868351519722561,"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."}}