{"id":"W4243585391","doi":"10.29173/cais692","title":"Music Recommender Systems and Genre Bias","year":2013,"lang":"fr","type":"article","venue":"Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI","topic":"Music and Audio Processing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Recommender system; Computer science; Categorization; Humanities; Art; Information retrieval; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.001005329,0.0004841601,0.0007916774,0.0001906045,0.0003002349,0.01099096,0.002528154,0.0003277126,0.000104628],"category_scores_gemma":[0.006695483,0.0003850675,0.0001886302,0.0007028069,0.0008879838,0.02186109,0.001624319,0.0005067807,0.00001918783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006986255,"about_ca_system_score_gemma":0.0004339026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001526384,"about_ca_topic_score_gemma":0.00001093772,"domain_scores_codex":[0.9969732,0.00007032015,0.0008822745,0.0006599729,0.0006249341,0.0007892887],"domain_scores_gemma":[0.9540657,0.0002487117,0.001428162,0.0003550476,0.04359705,0.0003052771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007567427,0.0006012642,0.09865197,0.008199283,0.0005349212,0.000006745119,0.1935409,0.00003437553,0.01983572,0.1655388,0.1955977,0.3173827],"study_design_scores_gemma":[0.002884968,0.001325264,0.1596538,0.0102295,0.0005779268,0.0008384709,0.02180475,0.0588599,0.0296749,0.03759601,0.6737037,0.002850821],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9508934,0.00599541,0.001202996,0.0233517,0.001495101,0.0007829586,0.00007605775,0.00007556775,0.01612683],"genre_scores_gemma":[0.9892554,0.0004917861,0.002365161,0.001104106,0.0003045818,0.00004813489,0.000001443091,0.00003484491,0.006394509],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.478106,"threshold_uncertainty_score":0.9998601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07285352405953807,"score_gpt":0.251277983106704,"score_spread":0.1784244590471659,"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."}}