{"id":"W7097225146","doi":"","title":"IDENTIFIERS *Canada; IFLA 1974; Library Developme.,t; Library Statistics","year":2016,"lang":"en","type":"article","venue":"","topic":"Library Science and Administration","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Subject (documents); Identifier; Table (database); Library automation; Distribution (mathematics); Information system; Automation","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"not_applicable","genre":"other","about_ca_system":false,"about_ca_topic":true,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["insufficient_payload"],"domain":null,"study_design":"not_applicable","genre":"other","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001291606,0.001675769,0.001100807,0.02237087,0.006569594,0.004672036,0.00221079,0.0009661484,0.1581042],"category_scores_gemma":[0.01247852,0.001020737,0.0004360703,0.05614849,0.001181079,0.001899677,0.001227044,0.00206405,0.08724073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06013992,"about_ca_system_score_gemma":0.1115386,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.9805977,"about_ca_topic_score_gemma":0.9792466,"domain_scores_codex":[0.9955113,0.0002082628,0.0002928586,0.0003559014,0.002901582,0.0007301428],"domain_scores_gemma":[0.9759376,0.001179966,0.001293464,0.0005848258,0.01955963,0.001444441],"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":[0.00001550649,0.000008673544,0.001676805,0.0001677588,0.000003568884,0.00001463279,0.00008258413,0.0001055278,0.0000210306,0.003039381,0.980321,0.01454356],"study_design_scores_gemma":[0.000005536371,0.00000402863,0.009831665,0.000148758,0.000003418819,0.00002020712,0.000167559,0.00009997886,0.00006668068,0.0002328026,0.9894046,0.0000148622],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.00139878,0.002125648,0.0005451296,0.001683509,0.0009434117,0.0002716822,0.7902805,0.0006646643,0.2020867],"genre_scores_gemma":[0.01160757,0.005256477,0.002706505,0.000846063,0.0002751049,0.0006787158,0.3838886,0.0005935506,0.5941474],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9805977,"threshold_uncertainty_score":0.5289112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01660621376468223,"score_gpt":0.2481939414455485,"score_spread":0.2315877276808663,"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."}}