{"id":"W4408657981","doi":"10.1121/2.0001994","title":"Understanding melodic transitions: A neuro-acoustical study with Indian Classical Music","year":2024,"lang":"en","type":"article","venue":"Proceedings of meetings on acoustics","topic":"Neuroscience and Music Perception","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Melody; Computer science; Speech recognition; Acoustics; Physics; Art; Visual arts; Musical","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001973754,0.0002187035,0.0001849145,0.0004053757,0.0006817556,0.0009218169,0.000424201,0.0003494714,0.002930713],"category_scores_gemma":[0.001376617,0.0001724372,0.0001855001,0.0005036401,0.0009255018,0.0004412033,0.0006536171,0.0005381592,0.0003451046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002309383,"about_ca_system_score_gemma":0.0003591538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008482989,"about_ca_topic_score_gemma":0.01356297,"domain_scores_codex":[0.999911,0.00001727776,0.00000424006,0.00002801954,0.00001718196,0.00002224739],"domain_scores_gemma":[0.9997368,0.0001183912,0.00002779944,0.00003082889,0.00004131622,0.00004484132],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.002657671,0.0007788045,0.04502891,0.0005971208,0.0001177975,0.001338922,0.02377007,0.001684451,0.8227739,0.00379051,0.001195654,0.09626618],"study_design_scores_gemma":[0.000125936,0.001014398,0.9126616,0.0000651316,0.000221606,0.001871533,0.02350162,0.009827814,0.03767663,0.005558403,0.007374359,0.0001010616],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931071,0.0001995885,0.002054054,0.00006631588,0.000009837143,0.00003147897,0.00009298226,0.00002121909,0.004417365],"genre_scores_gemma":[0.9978163,0.0001146403,0.001112607,0.00004566209,0.000006247035,0.00001367148,0.0000691047,0.00001397682,0.0008076055],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008482989,"threshold_uncertainty_score":0.01686722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09143766886586507,"score_gpt":0.2874314455880859,"score_spread":0.1959937767222208,"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."}}