{"id":"W2551551808","doi":"10.1145/2980179.2980240","title":"Gesture3D","year":2016,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Human Motion and Animation","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Gesture; Computer science; Character (mathematics); Artificial intelligence; Computer vision; Perception; Projection (relational algebra); Human–computer interaction; Computer graphics (images); Mathematics","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":[0.0005761083,0.002808016,0.0012095,0.00121147,0.0008932413,0.003714767,0.003040459,0.002671418,0.3170117],"category_scores_gemma":[0.001796131,0.001088585,0.001826884,0.00104411,0.0007664246,0.002702509,0.004751419,0.002011173,0.1854662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007562649,"about_ca_system_score_gemma":0.0008059065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005314453,"about_ca_topic_score_gemma":0.008895558,"domain_scores_codex":[0.9991097,0.0001041514,0.00008172814,0.0001770058,0.0004103073,0.0001171665],"domain_scores_gemma":[0.9995736,0.00006944448,0.00001982194,0.0001849394,0.00008716156,0.00006512939],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000855106,0.00009275898,0.0007181995,0.001309351,0.0001047667,0.0006989957,0.0004516064,0.005975366,0.02351244,0.02973687,0.5641252,0.3724193],"study_design_scores_gemma":[0.0001087969,0.00007692029,0.000561284,0.0001261317,0.00002977631,0.0005638931,0.0001016381,0.01427741,0.009746968,0.009347514,0.9649569,0.0001027411],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.003687385,0.002701,0.4044451,0.00085961,0.001873958,0.0007650161,0.03328555,0.2519184,0.3004639],"genre_scores_gemma":[0.1002515,0.003652257,0.2848987,0.002380308,0.0004165933,0.002111665,0.1153208,0.05838694,0.4325811],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.3170117,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01676133304867727,"score_gpt":0.2157769435008064,"score_spread":0.1990156104521291,"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."}}