{"id":"W4393401667","doi":"10.5281/zenodo.1219621","title":"A Canadian French Emotional Speech Dataset","year":2018,"lang":"en","type":"dataset","venue":"Figshare","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Speech recognition; Computer science; Psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001370164,0.004318192,0.001585652,0.004109365,0.003381803,0.00220116,0.003605393,0.002915066,0.05423236],"category_scores_gemma":[0.004959835,0.0005128479,0.001722237,0.003814032,0.0007981627,0.001200861,0.002099771,0.002067194,0.06595744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005613825,"about_ca_system_score_gemma":0.007672955,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.587678,"about_ca_topic_score_gemma":0.6865555,"domain_scores_codex":[0.9979327,0.0003401682,0.0001192721,0.0005015846,0.0007109075,0.0003953549],"domain_scores_gemma":[0.9972416,0.0003506255,0.00006054069,0.0004221279,0.001713377,0.0002117395],"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":[0.0002022752,0.00006098175,0.0008422142,0.000368686,0.00005374819,0.0001403785,0.00007464902,0.000509989,0.000805693,0.0004693917,0.9773691,0.01910274],"study_design_scores_gemma":[0.0002175399,0.00008814438,0.02122356,0.0003849494,0.0001072796,0.0005828853,0.0004877708,0.003982069,0.002266561,0.0006811956,0.9698178,0.0001601495],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003512777,0.0007430105,0.001029378,0.0003344829,0.0002651095,0.0002117269,0.9837731,0.002587253,0.00754313],"genre_scores_gemma":[0.002808274,0.0001533263,0.001225404,0.0001100142,0.00003158706,0.000239212,0.9910561,0.0001459077,0.004230124],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.412322,"threshold_uncertainty_score":0.8295006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04705013687903825,"score_gpt":0.2665401403992551,"score_spread":0.2194900035202168,"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."}}