{"id":"W1989093543","doi":"10.1145/2808196.2811639","title":"ETS System for AV+EC 2015 Challenge","year":2015,"lang":"en","type":"article","venue":"","topic":"Music and Audio Processing","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Computer Research Institute of Montréal; École de Technologie Supérieure","funders":"","keywords":"Computer science; Feature (linguistics); Modalities; Artificial intelligence; Artificial neural network; Random forest; Modality (human–computer interaction); Set (abstract data type); Pattern recognition (psychology); Speech recognition","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":[0.0003249282,0.00007121856,0.0001017134,0.00003068957,0.00005999028,0.0001091153,0.0004176953,0.00003751878,0.000004084411],"category_scores_gemma":[0.00001809229,0.00005443859,0.00002923263,0.00008263342,0.00001082709,0.0003202381,0.0001074698,0.00003330147,0.0001124578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003522284,"about_ca_system_score_gemma":0.0000961054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001001561,"about_ca_topic_score_gemma":0.000004575331,"domain_scores_codex":[0.9993163,0.00001314963,0.0001129786,0.0002134971,0.0001588543,0.0001851863],"domain_scores_gemma":[0.9994408,0.00002459645,0.00004432636,0.0002568344,0.0001131347,0.0001203428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00000828272,0.00006868928,0.00003589247,0.0002759617,0.00001816762,0.00001366954,0.00304246,0.00004733589,0.0001355703,0.4760053,0.3490382,0.1713104],"study_design_scores_gemma":[0.002350777,0.0003585793,0.00005950907,0.0002159466,0.00001436515,0.00006897039,0.001109054,0.2635147,0.006863052,0.01524876,0.7094522,0.0007441157],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0003321645,0.0003927874,0.9100583,0.004678085,0.0005990845,0.0001091758,5.235191e-7,0.000267232,0.08356266],"genre_scores_gemma":[0.9142457,0.00000195721,0.0806151,0.0007407919,0.0002587065,0.00002554214,8.079296e-7,0.000007603006,0.004103825],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9139135,"threshold_uncertainty_score":0.2219941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07841280843591787,"score_gpt":0.2914930587223466,"score_spread":0.2130802502864287,"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."}}