{"id":"W4409995859","doi":"10.47513/mmd.v17i2.969","title":"When Music is Enough","year":2025,"lang":"en","type":"article","venue":"Music and Medicine","topic":"Music Technology and Sound Studies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Wilfrid Laurier University; University Health Network","funders":"","keywords":"Humanities; Art; Political science","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":[0.0001782272,0.0001036873,0.0002076142,0.0001202408,0.0002114263,0.00001214156,0.0003057886,0.00007365928,0.0001397742],"category_scores_gemma":[0.00006245622,0.00007385023,0.00001915838,0.0002528381,0.0002842203,0.00007450215,0.0002576618,0.0001277211,0.00001163721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001053126,"about_ca_system_score_gemma":0.00002765562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007567979,"about_ca_topic_score_gemma":0.00003372651,"domain_scores_codex":[0.999281,0.00001533985,0.0001397092,0.0002778671,0.0001039685,0.0001820828],"domain_scores_gemma":[0.9994619,0.0000731177,0.00002926538,0.0003626735,0.00003530311,0.00003767286],"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":[0.000002662231,0.00001570528,0.0004567256,0.00002429219,0.00003651152,0.00001261218,0.01061614,3.510321e-8,0.00008433637,0.3721339,0.4809393,0.1356778],"study_design_scores_gemma":[0.0007007587,0.00009163468,0.005072183,0.00009249976,0.00002435186,0.00001021525,0.0004742429,0.0002844764,0.00007685432,0.1329925,0.8600773,0.0001029496],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09498282,0.01596237,0.3513188,0.2679998,0.003861701,0.0004110645,0.000002134267,0.0007896801,0.2646717],"genre_scores_gemma":[0.9388556,0.0002662729,0.00361664,0.04003128,0.0001933877,0.00001928344,0.000001026834,0.000003842676,0.01701268],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8438728,"threshold_uncertainty_score":0.3011525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02491892010356431,"score_gpt":0.2551020149624061,"score_spread":0.2301830948588418,"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."}}