{"id":"W2573305672","doi":"10.5281/zenodo.1417072","title":"Automatic Music Recommendation Systems: Do Demographic, Profiling, And Contextual Features Improve Their Performance?.","year":2016,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Music and Audio Processing","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Profiling (computer programming); Computer science; Recommender system; Data science; Information retrieval; Operating system","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":[0.002114809,0.0009194722,0.001682911,0.001459889,0.0007994088,0.001266522,0.001316362,0.001442617,0.005308986],"category_scores_gemma":[0.008095824,0.0003918443,0.0005719507,0.001498199,0.0001573297,0.001407395,0.0006120346,0.0008139496,0.008052425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002538897,"about_ca_system_score_gemma":0.0005357104,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008983281,"about_ca_topic_score_gemma":0.02214742,"domain_scores_codex":[0.9991141,0.0002870942,0.00007200721,0.0002559283,0.0001559574,0.0001149002],"domain_scores_gemma":[0.9974169,0.001196681,0.0001247672,0.0004543024,0.0005604826,0.0002468844],"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":[0.003130983,0.001203694,0.05912745,0.0003193127,0.0005707694,0.0001143247,0.0001208805,0.007508607,0.01091893,0.0003561786,0.05797532,0.8586535],"study_design_scores_gemma":[0.001029871,0.002156018,0.1476193,0.0002045862,0.001376393,0.0009615156,0.000810174,0.7840389,0.027223,0.003701009,0.03058443,0.0002947218],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7434136,0.01655737,0.1739458,0.00448609,0.002617508,0.0006908488,0.01857511,0.02215549,0.01755823],"genre_scores_gemma":[0.8101267,0.0026096,0.1487868,0.0009061007,0.001280757,0.0002276038,0.022276,0.0005263478,0.01326001],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008983281,"threshold_uncertainty_score":0.01786196,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02586663884643603,"score_gpt":0.2208807204444249,"score_spread":0.1950140815979888,"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."}}