{"id":"W2266542750","doi":"10.25071/1708-6701.36610","title":"Making Noise: Toronto Public Library's Local Music Project","year":2013,"lang":"en","type":"article","venue":"CAML Review / Revue de l ACBM","topic":"Library Science and Administration","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Noise (video); Media studies; Library science; Sociology; Computer science; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.004699545,0.000618566,0.0005116023,0.001981062,0.01242489,0.01067937,0.002017589,0.003545142,0.04547446],"category_scores_gemma":[0.009014455,0.000382918,0.0004214895,0.004385419,0.005355066,0.002266296,0.005395974,0.002221311,0.005706681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04022216,"about_ca_system_score_gemma":0.1213689,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8448588,"about_ca_topic_score_gemma":0.9521686,"domain_scores_codex":[0.9953805,0.0009231998,0.0001021186,0.0002342775,0.00210283,0.00125694],"domain_scores_gemma":[0.9922523,0.00138919,0.0003052789,0.0003977936,0.002428298,0.003227153],"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":[0.0001744854,0.00008711719,0.003544181,0.001355585,0.00004348888,0.0003145334,0.01510032,0.0002957186,0.0003687872,0.02034664,0.8452713,0.1130979],"study_design_scores_gemma":[0.0000474781,0.00007798591,0.02731825,0.00101535,0.0000847867,0.00005282611,0.0530061,0.00006349673,0.0004136746,0.0009135845,0.9169667,0.00003980112],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.07053266,0.08619502,0.0009198877,0.2298605,0.005683794,0.0006788599,0.005619738,0.0005254269,0.5999841],"genre_scores_gemma":[0.3346666,0.0586624,0.001234657,0.01429457,0.001384396,0.0004470917,0.003298373,0.0003245593,0.5856874],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1551412,"threshold_uncertainty_score":0.3121098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0835876624328473,"score_gpt":0.3392267403319832,"score_spread":0.2556390778991359,"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."}}