{"id":"W7096473932","doi":"","title":"National Library of Canada Cataloguing in Publication Data","year":2003,"lang":"en","type":"article","venue":"","topic":"Library Science and Information Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); National library; Corporation; Christian ministry; Product (mathematics); Service (business)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001723597,0.00207271,0.003399687,0.02277563,0.005648905,0.01171531,0.003898361,0.002243358,0.6075295],"category_scores_gemma":[0.01823333,0.001294625,0.0007696174,0.06300179,0.00131407,0.004614478,0.001829796,0.002059445,0.618325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02272803,"about_ca_system_score_gemma":0.1052851,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.8267577,"about_ca_topic_score_gemma":0.8354896,"domain_scores_codex":[0.9957708,0.0001252563,0.0004386968,0.0003599043,0.0028232,0.000482181],"domain_scores_gemma":[0.9598892,0.001416875,0.0009019632,0.00184696,0.03403286,0.001912243],"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":[0.00001009539,0.000007953037,0.0001195994,0.0002743468,0.000002530911,0.00001240637,0.00001907607,0.00001922171,0.00002961186,0.0006996404,0.9860958,0.01270972],"study_design_scores_gemma":[0.000007513393,0.000002655697,0.0009945008,0.00026531,0.000005419048,0.00001028975,0.00004275537,0.00002404001,0.00003933756,0.0001869219,0.9984058,0.00001555212],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0001755859,0.001463111,0.0003187218,0.001700231,0.001040597,0.0003389057,0.6132829,0.001348419,0.3803314],"genre_scores_gemma":[0.001515187,0.007032463,0.001668767,0.001202256,0.0002376131,0.0004054894,0.4434654,0.0009798853,0.543493],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8267577,"threshold_uncertainty_score":0.5598115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03641626417610754,"score_gpt":0.2205704693714768,"score_spread":0.1841542051953692,"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."}}