{"id":"W2757249210","doi":"10.18061/emr.v12i1-2.5410","title":"In Search of the Golden Age Hip-Hop Sound (1986–1996)","year":2017,"lang":"en","type":"article","venue":"Empirical Musicology Review","topic":"Music and Audio Processing","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Centre for Interdisciplinary Research in Music Media and Technology; McGill University","keywords":"Musical; Loudness; Sound change; Popular music; Harmony (color); Scholarship; Sound (geography); Salient; History; Linguistics; Speech recognition; Computer science; Literature; Art; Acoustics; Visual arts; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009351642,0.0001359397,0.0004798401,0.00003990652,0.0002640849,0.00009446035,0.002488043,0.0001001416,0.000132251],"category_scores_gemma":[0.0004382889,0.00008659261,0.0001356903,0.000296164,0.0003908077,0.0003085388,0.001189444,0.0003451076,0.00008881175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003944855,"about_ca_system_score_gemma":0.0001666506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003003552,"about_ca_topic_score_gemma":0.00004395152,"domain_scores_codex":[0.998359,0.0002834149,0.0003945456,0.0003851846,0.0002430036,0.0003348999],"domain_scores_gemma":[0.998154,0.0001677633,0.0002596662,0.001287063,0.00006176877,0.00006976277],"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":[0.00000930519,0.0004463185,0.07034475,0.004033936,0.00005083795,0.0002898969,0.002060873,0.000006562868,0.0007656617,0.02140454,0.6896892,0.2108982],"study_design_scores_gemma":[0.0008012668,0.0001300959,0.2322756,0.003352613,0.00005111769,0.00008944645,0.000007135674,0.0004118418,0.00037065,0.0250458,0.7370053,0.0004591274],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1912265,0.05526721,0.007127068,0.709833,0.00226713,0.001438951,0.000002489565,0.00007859796,0.03275906],"genre_scores_gemma":[0.7396863,0.003412933,0.003177899,0.251556,0.0002683062,0.00005948138,7.037169e-7,0.00001802935,0.001820388],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.5484597,"threshold_uncertainty_score":0.4623445,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1510335986881979,"score_gpt":0.4002782646324989,"score_spread":0.249244665944301,"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."}}