{"id":"W4233659602","doi":"10.32920/14638968","title":"Musings on Collection Analysis and Its Utility in Modern Collection Development","year":2021,"lang":"en","type":"article","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":"Data collection; Measure (data warehouse); Collection development; Focus (optics); Data science; Computer science; Knowledge management; World Wide Web; Sociology; Database; Social science","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":[],"consensus_categories":[],"category_scores_codex":[0.0001529238,0.000116634,0.0001701649,0.0006460833,0.0002300639,0.0003645641,0.0001181246,0.00005648693,0.00007973328],"category_scores_gemma":[0.000044909,0.0001125108,0.00004194709,0.00533629,0.000009125099,0.0007378486,0.0001515253,0.00007303519,0.000008738639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001104487,"about_ca_system_score_gemma":0.0003050746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002512865,"about_ca_topic_score_gemma":0.0005866927,"domain_scores_codex":[0.9988049,0.00005619182,0.0002421316,0.0004600767,0.0002585769,0.0001781302],"domain_scores_gemma":[0.9995826,0.00007399027,0.00004472356,0.0001403041,0.00008098118,0.00007743651],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004633831,0.00236861,0.4905847,0.0001442754,0.00153511,0.0002293618,0.03512899,0.002385615,0.002463562,0.02094745,0.0117887,0.4319603],"study_design_scores_gemma":[0.0007823918,0.00005905027,0.4992217,0.00001880937,0.00001793085,0.00001421377,0.0001856365,0.4243792,0.06483989,0.002110589,0.007960679,0.0004098349],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8573024,0.00007986211,0.08173576,0.0005239982,0.0001255202,0.0001350569,2.901148e-7,0.0001549256,0.05994223],"genre_scores_gemma":[0.9701146,0.00001974387,0.007172634,0.0003140635,0.000006822575,0.00001695231,0.000004272474,0.000003695632,0.0223472],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4315504,"threshold_uncertainty_score":0.4588057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02332222516532372,"score_gpt":0.220755736596145,"score_spread":0.1974335114308213,"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."}}