{"id":"W4392985400","doi":"10.32920/25413001","title":"Modeling Music Emotion Judgments Using Machine Learning Methods","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Music and Audio Processing","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Rehabilitation Institute; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Artificial intelligence; Psychology; Cognitive psychology; Emotion detection; Machine learning; Emotion recognition","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001982959,0.0006085635,0.0005379149,0.0005755951,0.0002873427,0.001028671,0.0007674405,0.0008563114,0.001495289],"category_scores_gemma":[0.008759391,0.0003886235,0.0007996469,0.0004344161,0.0003448951,0.0007499112,0.0004066498,0.001106795,0.000356098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006574541,"about_ca_system_score_gemma":0.0003888746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004925744,"about_ca_topic_score_gemma":0.004172086,"domain_scores_codex":[0.9992352,0.0003617951,0.00003487947,0.0002089504,0.00009433916,0.00006487986],"domain_scores_gemma":[0.9969944,0.002392062,0.0002031693,0.0001279175,0.0002377334,0.00004486859],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002631226,0.000167418,0.01031194,0.0000525679,0.0001482138,0.00008997428,0.0002698085,0.897996,0.005751222,0.001882846,0.0006363489,0.08243059],"study_design_scores_gemma":[0.000001807832,0.000008277706,0.000697092,0.00000142876,0.000002541033,0.000003223171,0.000005440048,0.9985254,0.0001986028,0.0005213129,0.00003215595,0.000002730013],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3923826,0.0002334034,0.6039014,0.0003457075,0.00004992434,0.000134392,0.000231702,0.0007371955,0.00198371],"genre_scores_gemma":[0.9353781,0.00005873705,0.06301393,0.00004885655,0.00003245392,0.000135871,0.0001867423,0.00002601883,0.001119286],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004925744,"threshold_uncertainty_score":0.01048702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1221948991033433,"score_gpt":0.3678108533166406,"score_spread":0.2456159542132973,"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."}}