{"id":"W4210981237","doi":"10.1145/965500.965503","title":"EMOCAP","year":2003,"lang":"en","type":"article","venue":"","topic":"Human Motion and Animation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Motion capture; Animation; Sketch; Character animation; Computer science; Relevance (law); Trademark; Mood; Character (mathematics); Movement (music); Motion (physics); Human–computer interaction; Computer animation; Artificial intelligence; Psychology; Aesthetics; Art; Computer graphics (images); Social psychology","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":[0.000521342,0.001134208,0.0005038655,0.0008175697,0.0004517736,0.001389991,0.001516409,0.001448137,0.1316553],"category_scores_gemma":[0.001916238,0.0005214981,0.0006120084,0.000490533,0.0002014716,0.001393741,0.002164499,0.0009061697,0.06605551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000259935,"about_ca_system_score_gemma":0.0003657104,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001056871,"about_ca_topic_score_gemma":0.001748021,"domain_scores_codex":[0.9996872,0.00005024384,0.00002196894,0.00006876563,0.0001304861,0.00004138901],"domain_scores_gemma":[0.999535,0.0001277702,0.00001899799,0.0001158542,0.000148679,0.00005374671],"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":[0.0006650699,0.0001395809,0.0008115237,0.0007502304,0.00006748147,0.0002688056,0.0002120858,0.002091005,0.01960684,0.01201218,0.7242254,0.2391496],"study_design_scores_gemma":[0.0001087695,0.0001209223,0.002297606,0.0001366183,0.0000458117,0.0005274768,0.00005416765,0.02143739,0.01562847,0.007450514,0.952102,0.00009037439],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.009487473,0.001403073,0.3659771,0.0009119965,0.001383687,0.0009327619,0.04642362,0.2623928,0.3110874],"genre_scores_gemma":[0.1016345,0.002265627,0.2297082,0.004534773,0.0005474406,0.003518656,0.1403253,0.0386204,0.4788452],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1316553,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007270651611774761,"score_gpt":0.1733446582431493,"score_spread":0.1660740066313745,"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."}}