{"id":"W2337812952","doi":"10.14288/1.0093087","title":"Ensemble pitch and rhythm error discrimination : the identification and selection of predictors","year":2011,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Music and Audio Processing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Rhythm; Selection (genetic algorithm); Identification (biology); Computer science; Artificial intelligence; Biology; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002173517,0.000737934,0.000500608,0.0008057764,0.0003134694,0.0008182216,0.0004161696,0.0005482874,0.003180138],"category_scores_gemma":[0.01590301,0.0002704083,0.0004123712,0.0006674239,0.000365064,0.0006214944,0.0008693252,0.001179544,0.0007238925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001793801,"about_ca_system_score_gemma":0.0007672763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004387537,"about_ca_topic_score_gemma":0.003927525,"domain_scores_codex":[0.9989753,0.0003432744,0.00006721663,0.0001846143,0.0002686199,0.0001609736],"domain_scores_gemma":[0.9879254,0.007687599,0.001744257,0.0008445105,0.0008019422,0.0009963399],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001393545,0.00009167671,0.9902678,0.000006365064,0.00003502221,0.00005350562,0.0000989035,0.0003223391,0.0003750597,0.00005280913,0.00008641956,0.008470782],"study_design_scores_gemma":[0.000007622314,0.0001330823,0.9953322,0.000008385992,0.00002603446,0.0001274996,0.0001403709,0.003592475,0.0003241211,0.0001508868,0.0001492614,0.000008101949],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975539,0.0001357135,0.001533081,0.00004374562,0.000008529498,0.000009111872,0.0001414564,0.00002115735,0.0005532678],"genre_scores_gemma":[0.9986253,0.0000613626,0.0006539784,0.000008775024,0.000008996423,0.00001319924,0.0002461797,0.000009161728,0.0003731281],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004387537,"threshold_uncertainty_score":0.01149476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01561605368401825,"score_gpt":0.1790727471224302,"score_spread":0.163456693438412,"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."}}