{"id":"W7097874746","doi":"","title":"Canadian Cataloguing in Publication Data","year":2000,"lang":"en","type":"article","venue":"","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Field (mathematics); Government (linguistics); Data collection; Public policy; Ethical issues; MEDLINE","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":[0.01349748,0.003026196,0.005228003,0.09412383,0.01150783,0.02900237,0.005450642,0.003292077,0.3195056],"category_scores_gemma":[0.1452811,0.002338788,0.002039487,0.2088007,0.002804127,0.007125533,0.005739858,0.004368672,0.2420914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05987843,"about_ca_system_score_gemma":0.375476,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.8849829,"about_ca_topic_score_gemma":0.8676465,"domain_scores_codex":[0.9586319,0.001530078,0.0081244,0.002968089,0.02470359,0.004042097],"domain_scores_gemma":[0.7028777,0.01952486,0.0148607,0.02160782,0.223325,0.01780399],"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":[0.00002626828,0.00001145591,0.0008134517,0.001298822,0.00001718165,0.00003088178,0.0001062001,0.00004552555,0.00007104399,0.004192239,0.9671313,0.02625564],"study_design_scores_gemma":[0.0000108647,0.000004046004,0.004080848,0.0007577025,0.00002060059,0.0000182703,0.0001253806,0.00004582102,0.00009261258,0.0005272774,0.9942744,0.00004202316],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0004935853,0.002930688,0.0006411753,0.005435586,0.004427131,0.0005607806,0.8810166,0.001640332,0.1028542],"genre_scores_gemma":[0.006149495,0.0133018,0.005939831,0.001689241,0.0006248084,0.001131447,0.8122175,0.001345904,0.1576],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8849829,"threshold_uncertainty_score":0.9706427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8051501648126124,"score_gpt":0.6217667223505557,"score_spread":0.1833834424620566,"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."}}