{"id":"W4235489864","doi":"10.1002/meet.2009.1450460366","title":"Answering the unanswered question? Contextualizing a holistic theoretical framework for cross‐genre music information retrieval","year":2009,"lang":"en","type":"article","venue":"Proceedings of the American Society for Information Science and Technology","topic":"Music and Audio Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Relation (database); Music information retrieval; Computer science; Information retrieval; Musical; Literature; Art","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.001694464,0.0001294406,0.0001932172,0.0001594106,0.00109084,0.0006284819,0.001360359,0.00008518667,4.315525e-7],"category_scores_gemma":[0.00214373,0.00008218162,0.0001119408,0.002767452,0.003168075,0.004424379,0.0002428993,0.0001917726,6.674459e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007216499,"about_ca_system_score_gemma":0.0001817584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001905165,"about_ca_topic_score_gemma":4.807714e-8,"domain_scores_codex":[0.998588,0.000002459039,0.0004173288,0.000172293,0.00044018,0.0003797069],"domain_scores_gemma":[0.9974401,0.0001361579,0.0007533637,0.0001973461,0.001425167,0.00004784908],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001332752,0.000005268137,0.0001152975,0.0000397638,0.000005451067,2.757182e-9,0.002751655,0.000004303824,0.001568258,0.9097689,0.0002702321,0.08545759],"study_design_scores_gemma":[0.001052289,0.0008000102,0.005435032,0.0002821452,0.00005393747,0.00004682949,0.01802596,0.1091931,0.03874906,0.811227,0.01458536,0.0005492535],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3737371,0.00003945062,0.6066217,0.01796465,0.0001616528,0.0008260818,0.0000107839,0.0002102422,0.0004283968],"genre_scores_gemma":[0.9390757,0.0000182657,0.05583689,0.00500414,0.00002600303,0.00003246369,7.89446e-7,0.000002519474,0.000003206122],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5653387,"threshold_uncertainty_score":0.9995447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01669322162443783,"score_gpt":0.3055293496963888,"score_spread":0.288836128071951,"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."}}