{"id":"W4242958314","doi":"10.32920/14638968.v1","title":"Musings on Collection Analysis and Its Utility in Modern Collection Development","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Library Collection Development and Digital Resources","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Collection development; Data collection; Measure (data warehouse); Focus (optics); Data science; Computer science; Library science; Sociology; Social science; Database","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0003117431,0.0003196452,0.0004715731,0.001728762,0.0002726222,0.001282707,0.0003694937,0.0002613347,0.00007958252],"category_scores_gemma":[0.00005800694,0.0003200588,0.0001237166,0.004451223,0.00001707566,0.000716356,0.001183395,0.0003466415,0.0000046093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003286641,"about_ca_system_score_gemma":0.0008777126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001568862,"about_ca_topic_score_gemma":0.001258588,"domain_scores_codex":[0.9974678,0.0001189185,0.0005185106,0.00111927,0.0004932708,0.0002822142],"domain_scores_gemma":[0.9991162,0.0001024892,0.0001657604,0.0003506507,0.0001389216,0.0001259577],"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":[0.0009550833,0.004572415,0.3498193,0.001405149,0.007244805,0.0003532549,0.1141465,0.03116621,0.0005154075,0.005268317,0.01202258,0.4725309],"study_design_scores_gemma":[0.0005526179,0.00005119119,0.269246,0.0001106577,0.00004933819,0.000006587612,0.0002068746,0.7162946,0.009499609,0.001666193,0.001528328,0.0007880026],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8339588,0.0001950118,0.1323142,0.0003657752,0.0004199182,0.0004506948,0.000001036494,0.0002709184,0.03202361],"genre_scores_gemma":[0.9743422,0.00007810305,0.01268265,0.0002368037,0.00001696393,0.00008838376,0.00003145759,0.00001031693,0.01251308],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6851284,"threshold_uncertainty_score":0.9999251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03049811207567745,"score_gpt":0.2333111384656953,"score_spread":0.2028130263900179,"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."}}