{"id":"W6991064247","doi":"","title":"2013 Fall Library Connections: UFV Library Newsletter","year":2013,"lang":"en","type":"article","venue":"Arca (British Columbia Electronic Library Network)","topic":"Library Collection Development and Digital Resources","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Digital library; Library classification; Library automation; National library","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["scholarly_communication","insufficient_payload"],"category_scores_codex":[0.00009531419,0.0004799458,0.0005861917,0.0002146655,0.0009286453,0.01920409,0.002754303,0.0003164847,0.1531518],"category_scores_gemma":[0.00001491216,0.0007366026,0.0003420668,0.00315096,0.0001774297,0.04420784,0.001898018,0.00085197,0.001257896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004711915,"about_ca_system_score_gemma":0.001053811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001010315,"about_ca_topic_score_gemma":0.0006937342,"domain_scores_codex":[0.9945008,0.000309105,0.000916875,0.001416334,0.0005853789,0.002271532],"domain_scores_gemma":[0.9975806,0.0004243893,0.0002768516,0.001033335,0.00003175808,0.0006530294],"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":[0.00001046159,0.0001497934,0.02348264,0.00001901184,0.000114891,0.00006491548,0.00004246245,0.00006259078,0.000001038979,0.04928051,0.9014111,0.02536062],"study_design_scores_gemma":[0.0005851652,0.0002684626,0.00231767,0.00008987213,0.000009359674,0.0001664116,0.00001097003,0.002778129,0.00003681748,0.3729146,0.6201045,0.000717983],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02343715,0.008530688,0.0004438605,0.03255471,0.001668239,0.002233711,0.00002616567,0.007613421,0.9234921],"genre_scores_gemma":[0.6138159,0.003725531,0.01163017,0.03555861,0.001912801,0.0007232002,0.0003415979,0.0002607734,0.3320314],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.5914606,"threshold_uncertainty_score":0.9995198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003903425657337293,"score_gpt":0.1498601402003593,"score_spread":0.145956714543022,"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."}}