{"id":"W1571854457","doi":"","title":"Music in Motion . The Automated Transcription for Indian Music(AUTRIM).","year":2014,"lang":"en","type":"article","venue":"MUSICultures","topic":"Music and Audio Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Transcription (linguistics); Motion (physics); Computer science; Artificial intelligence; Linguistics; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001208151,0.001429081,0.0007328811,0.003208084,0.0007420279,0.001856016,0.001349571,0.001383693,0.05177402],"category_scores_gemma":[0.003872379,0.0006670732,0.0005057729,0.002404322,0.0005061055,0.001481489,0.003108061,0.0009500151,0.07035383],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003213949,"about_ca_system_score_gemma":0.0006775977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005806635,"about_ca_topic_score_gemma":0.01085445,"domain_scores_codex":[0.9986393,0.0002470105,0.00008963523,0.0002355968,0.0006769879,0.0001114439],"domain_scores_gemma":[0.9984848,0.0002823373,0.0001395181,0.0005048113,0.0003513462,0.0002372024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004849462,0.00004587124,0.001235313,0.0004485016,0.00004386978,0.0002197731,0.0001462535,0.0006364406,0.02354059,0.001477112,0.2977706,0.6739507],"study_design_scores_gemma":[0.0002814521,0.0003072813,0.02241164,0.000356198,0.000141049,0.001680328,0.0006661884,0.04104974,0.1147312,0.01042582,0.8077769,0.0001721734],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01632014,0.01079419,0.5053802,0.00146619,0.003218709,0.0005006485,0.09201992,0.307611,0.06268907],"genre_scores_gemma":[0.1185643,0.003729249,0.5185378,0.001143099,0.001732682,0.0006459731,0.2064142,0.02301438,0.1262184],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05177402,"threshold_uncertainty_score":0.1732014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02243246310594664,"score_gpt":0.2373750405969372,"score_spread":0.2149425774909906,"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."}}