{"id":"W7097073257","doi":"","title":"National Library 1*1 of Bibliothèque nationale du Canada Acquisitions and Acquisitions et","year":2015,"lang":"en","type":"article","venue":"","topic":"Library Collection Development and Digital Resources","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"National library; Government (linguistics); Information system; National interest","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":[],"consensus_categories":[],"category_scores_codex":[0.00008129729,0.00006465597,0.00006780286,0.0004440361,0.00007931862,0.0002881323,0.0002239747,0.00002121084,0.0002034542],"category_scores_gemma":[0.00006482757,0.00005879674,0.0000163059,0.001365949,0.0000283809,0.003311341,0.0002030992,0.00003062502,0.000005777902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000298737,"about_ca_system_score_gemma":0.00311789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002173289,"about_ca_topic_score_gemma":0.004035182,"domain_scores_codex":[0.9991999,0.00002491553,0.0001499455,0.0001419309,0.0003991384,0.00008412181],"domain_scores_gemma":[0.9994086,0.0002042693,0.00004361741,0.00007919308,0.0001397662,0.000124543],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002524356,0.00002803936,0.002710394,0.000002787318,0.00001007262,0.000002021761,0.0001664309,0.0001044547,0.00000621264,0.5291342,0.467726,0.0001068851],"study_design_scores_gemma":[0.001124967,0.0001011295,0.05492004,0.00002481523,0.00000398781,0.0001108803,0.0002062332,0.02075878,0.00231683,0.156088,0.763861,0.0004833129],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02742024,0.0002017933,0.01754973,0.01728209,0.0001785377,0.0001067467,0.00004582414,0.0001600595,0.937055],"genre_scores_gemma":[0.9503341,0.00002972347,0.01888261,0.005197991,0.00005906518,0.00001473898,0.00004543438,0.000006385276,0.02542998],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9229138,"threshold_uncertainty_score":0.5531003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01713960795237233,"score_gpt":0.2102432442410192,"score_spread":0.1931036362886469,"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."}}