{"id":"W2546231710","doi":"10.7202/1028596ar","title":"Étude préliminaire à l’élaboration d’un vocabulaire contrôlé en langue française pour le catalogue matière des bibliothèques publiques et scolaires","year":2015,"lang":"fr","type":"article","venue":"Documentation et bibliothèques","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Humanities; Political science; Art","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.02728176,0.0006596618,0.0006301561,0.01096171,0.005567638,0.01794886,0.001591049,0.001722983,0.01030609],"category_scores_gemma":[0.05947704,0.0007271091,0.0008816994,0.01514535,0.006453326,0.0119413,0.004918483,0.002415112,0.002664732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02107947,"about_ca_system_score_gemma":0.04417052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2778513,"about_ca_topic_score_gemma":0.3180115,"domain_scores_codex":[0.980561,0.007831428,0.003456993,0.001830841,0.005480294,0.0008395877],"domain_scores_gemma":[0.9242992,0.03113276,0.004557919,0.009226689,0.02947756,0.00130578],"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":[0.0002194239,0.000203776,0.05004687,0.003104146,0.0001359472,0.0008445538,0.1906709,0.001587401,0.01819246,0.4172722,0.0220987,0.2956237],"study_design_scores_gemma":[0.00004558384,0.0001147063,0.03961957,0.004365199,0.000161159,0.0006569979,0.08695395,0.00206646,0.006689584,0.01574722,0.8434067,0.0001728301],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.2905725,0.01254265,0.2468359,0.02735951,0.0009430731,0.003289008,0.009631217,0.001732881,0.4070932],"genre_scores_gemma":[0.7089216,0.006869112,0.2008806,0.002617321,0.0001909821,0.002849904,0.007517733,0.001079388,0.06907326],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9820511,"threshold_uncertainty_score":0.5524679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09274474865640686,"score_gpt":0.3355112269176303,"score_spread":0.2427664782612234,"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."}}