{"id":"W2390689188","doi":"10.82308/44846","title":"Automatic music classification with jMIR","year":2010,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Music and Audio Processing","field":"Computer Science","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Suite; Tying; Metadata; World Wide Web; Set (abstract data type); Music information retrieval; Data science; Information retrieval; Musical; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006656141,0.0003629862,0.0003035243,0.0002120118,0.001079745,0.0003229384,0.001380842,0.0002147031,0.0002130943],"category_scores_gemma":[0.0001516661,0.0003090687,0.00009587392,0.0009242212,0.0001298983,0.002180509,0.0002877271,0.0009502711,0.0004533826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001140638,"about_ca_system_score_gemma":0.00007077838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002075178,"about_ca_topic_score_gemma":0.0001128137,"domain_scores_codex":[0.9973062,0.0001161688,0.0004398592,0.0008856293,0.0006532911,0.0005987984],"domain_scores_gemma":[0.9977851,0.00012743,0.0003295751,0.001222624,0.000229684,0.0003056065],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005510078,0.0001139738,0.00008387335,0.00005829421,0.00002028123,0.00002498489,0.00001288199,0.00000467365,0.101672,0.2747596,0.0000180481,0.6232258],"study_design_scores_gemma":[0.005495916,0.0008707945,0.0577485,0.0009540356,0.0001833882,0.001217376,0.000216864,0.0751896,0.2725771,0.1887712,0.3914748,0.005300347],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9530064,0.00001613573,0.0003882655,0.0002749441,0.0006108879,0.0003771321,0.00001671415,0.0008918291,0.04441763],"genre_scores_gemma":[0.9590258,0.00000267463,0.03901607,0.001286829,0.00005176197,0.0001015402,0.00000674827,0.00004659677,0.0004619946],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6179255,"threshold_uncertainty_score":0.9999362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02308470257553307,"score_gpt":0.2335094472206267,"score_spread":0.2104247446450936,"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."}}