{"id":"W2612881451","doi":"10.25071/1708-6701.40280","title":"Building a Collection of Iranian Music at the University of Toronto Music Library","year":2017,"lang":"en","type":"article","venue":"CAML Review / Revue de l ACBM","topic":"Diverse Musicological Studies","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Discoverability; Collection development; Data collection; Library science; Process (computing); Selection (genetic algorithm); Visual arts; Political science; Computer science; Sociology; World Wide Web; Social science; Art","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":[0.009451621,0.0007135206,0.0007664749,0.01542483,0.02045898,0.006796659,0.002809258,0.001177447,0.02198365],"category_scores_gemma":[0.01512718,0.0007488549,0.000500015,0.01753809,0.005116843,0.002755826,0.007271443,0.001725684,0.004678493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02046701,"about_ca_system_score_gemma":0.05586552,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2433455,"about_ca_topic_score_gemma":0.5743712,"domain_scores_codex":[0.9929585,0.001706928,0.0004930827,0.0005545961,0.003704575,0.0005821854],"domain_scores_gemma":[0.9835755,0.003075903,0.001308413,0.002093999,0.007054863,0.002891419],"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":[0.000168158,0.0002968317,0.01310569,0.00344076,0.00006518464,0.003171669,0.2512592,0.0005287305,0.006528774,0.02606509,0.2521306,0.4432394],"study_design_scores_gemma":[0.00002488399,0.00009211447,0.02944501,0.001053365,0.0000288415,0.000441336,0.07799023,0.00009625017,0.0011939,0.0007360677,0.8888386,0.00005929156],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.289922,0.02775683,0.03694863,0.02635028,0.004386285,0.0242145,0.0299638,0.001676797,0.5587809],"genre_scores_gemma":[0.4669844,0.03388386,0.2003184,0.005004041,0.003015615,0.01286331,0.02500739,0.001199461,0.2517236],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2433455,"threshold_uncertainty_score":0.4838582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09549720916001582,"score_gpt":0.2334075669180828,"score_spread":0.1379103577580669,"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."}}