{"id":"W2737934051","doi":"10.7202/1040388ar","title":"La Division de la gestion de documents et des archives de l’Université de Montréal : un regard d’outre-Atlantique","year":2017,"lang":"fr","type":"article","venue":"Archives","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Art; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002662156,0.0006053149,0.0004179107,0.002965458,0.01674433,0.01868011,0.002620084,0.001824059,0.02398973],"category_scores_gemma":[0.007053919,0.0004625017,0.0004177986,0.008449074,0.01827021,0.007348748,0.008093462,0.003051617,0.001061523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.08841951,"about_ca_system_score_gemma":0.09311331,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.9256775,"about_ca_topic_score_gemma":0.9510061,"domain_scores_codex":[0.9962484,0.0008829584,0.0001082263,0.0004991851,0.001089668,0.001171589],"domain_scores_gemma":[0.9951179,0.0009276388,0.0004810815,0.0006013975,0.001268596,0.001603445],"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":[0.00007776624,0.00003704032,0.0103792,0.000220176,0.0000291694,0.0006339978,0.1617924,0.0006080699,0.001440807,0.7292516,0.02847757,0.06705214],"study_design_scores_gemma":[0.00002101728,0.00003902023,0.03529123,0.0003854726,0.00003969501,0.000278303,0.1142227,0.0004562195,0.001431845,0.02286782,0.8248776,0.00008891145],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2382213,0.01254117,0.01384779,0.08181655,0.000626506,0.0002439811,0.001737896,0.0003691175,0.6505956],"genre_scores_gemma":[0.8505544,0.00315431,0.004008575,0.001580162,0.0001639911,0.00009011866,0.0002652802,0.000151741,0.1400315],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9256775,"threshold_uncertainty_score":0.6415315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05345613959968627,"score_gpt":0.283907120356984,"score_spread":0.2304509807572978,"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."}}