{"id":"W2524652555","doi":"10.1145/2964284.2967204","title":"INRS Audiovisual Quality Dataset","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Image Processing Techniques","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Computer science; Quality (philosophy); Speech recognition; Artificial intelligence","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":[0.001754475,0.001844138,0.001412191,0.006007866,0.0006383565,0.001817323,0.002275997,0.001434779,0.03900645],"category_scores_gemma":[0.01049536,0.0003120111,0.001048365,0.006108741,0.0003471452,0.001128254,0.001961525,0.001012726,0.04450668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001271074,"about_ca_system_score_gemma":0.001280281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01705388,"about_ca_topic_score_gemma":0.01932978,"domain_scores_codex":[0.9963168,0.0005041836,0.0005946417,0.0006843017,0.001571423,0.0003286094],"domain_scores_gemma":[0.9927877,0.001397096,0.0006629597,0.001513635,0.003230034,0.0004085709],"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":[0.000504128,0.0001867018,0.008449503,0.001762624,0.0001313648,0.0002054012,0.00008280182,0.001897217,0.001438361,0.0006983742,0.9374976,0.04714592],"study_design_scores_gemma":[0.0003250619,0.0002004108,0.06275556,0.0006408897,0.0001274679,0.000569233,0.0003889358,0.004617672,0.00290803,0.001591109,0.9257007,0.0001749106],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003155763,0.0002951808,0.0008900131,0.0001187776,0.00008291796,0.00012354,0.9893441,0.001739105,0.00425064],"genre_scores_gemma":[0.004751186,0.0001244145,0.001276691,0.00005838897,0.00003053957,0.000254567,0.9921036,0.0001397531,0.001260783],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03900645,"threshold_uncertainty_score":0.1304895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03993526546755415,"score_gpt":0.3779546367234578,"score_spread":0.3380193712559036,"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."}}