{"id":"W2077639681","doi":"10.1109/iscas.2014.6865244","title":"Automatic age recommendation system for children's video content","year":2014,"lang":"en","type":"article","venue":"","topic":"Music and Audio Processing","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Novelty; Feature extraction; Classifier (UML); Speech recognition; Artificial intelligence; Cognition; Multimedia","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003701929,0.00006757515,0.0001031978,0.00003412584,0.0001231867,0.0002057392,0.0002862894,0.00002464167,0.00001736497],"category_scores_gemma":[0.00002695132,0.00005252493,0.00003032742,0.00006625101,0.000008092869,0.0004452776,0.00004525228,0.0000257963,0.00002310671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002428738,"about_ca_system_score_gemma":0.00001323147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001553311,"about_ca_topic_score_gemma":0.00000371176,"domain_scores_codex":[0.9993899,0.00003704656,0.0001588573,0.0002060112,0.00007324089,0.0001349741],"domain_scores_gemma":[0.9995598,0.00005354041,0.0000766716,0.0002172836,0.00004046429,0.00005223699],"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":[7.850959e-7,0.00002106477,0.0001084204,0.00006576225,0.000006749015,1.712426e-7,0.0001853696,0.000006735655,0.0003652244,0.07767081,0.002483375,0.9190855],"study_design_scores_gemma":[0.0006181236,0.0001166072,0.004076329,0.00007834374,0.000007872762,0.00001459098,0.00005179296,0.9856926,0.004165923,0.001355978,0.003626547,0.0001953574],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02238034,0.000003195678,0.9727458,0.001135428,0.0002564745,0.0001743695,5.067268e-7,0.0003886202,0.002915264],"genre_scores_gemma":[0.8701933,1.519627e-7,0.1282705,0.00122626,0.00008801281,0.00002437581,0.000009417558,0.000004664961,0.0001832971],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9856858,"threshold_uncertainty_score":0.2141904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03157680968447466,"score_gpt":0.2406106249944264,"score_spread":0.2090338153099518,"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."}}