{"id":"W7097195602","doi":"","title":"National Library 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; Context (archaeology)","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":[0.00008653685,0.00008284958,0.00006250378,0.0004508561,0.0001592046,0.0008414024,0.0002590095,0.00002523467,0.0002894401],"category_scores_gemma":[0.00006717953,0.00007551631,0.00001641438,0.001456582,0.00002383362,0.004833935,0.0002493792,0.00004355302,0.00002309197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005165901,"about_ca_system_score_gemma":0.003486501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002024749,"about_ca_topic_score_gemma":0.005953827,"domain_scores_codex":[0.9990845,0.00002936716,0.0001330487,0.0001941443,0.0004409692,0.0001179753],"domain_scores_gemma":[0.9993679,0.000203168,0.00003113295,0.00008877789,0.0001169995,0.000192041],"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":[0.000001568971,0.00001810067,0.001425943,0.000001138955,0.000007021363,0.000003896921,0.0001204504,0.00006834177,0.000001588162,0.4085942,0.5896547,0.0001030238],"study_design_scores_gemma":[0.0004947541,0.00003352171,0.01748555,0.000007466068,0.000001520397,0.00009272746,0.00008845581,0.01216931,0.0002456473,0.08011156,0.8889846,0.000284854],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0113763,0.0001796084,0.01893825,0.03385342,0.0002364376,0.0001053532,0.00003092555,0.000300195,0.9349795],"genre_scores_gemma":[0.870978,0.00004943335,0.02736443,0.02373276,0.0001808445,0.00004116398,0.0001019523,0.00001308196,0.07753835],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8596017,"threshold_uncertainty_score":0.8113663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01719046602219892,"score_gpt":0.2086002129379327,"score_spread":0.1914097469157337,"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."}}