{"id":"W2516032590","doi":"10.7202/1053550ar","title":"Le recensement des documents audiovisuels de langue française au Canada","year":2018,"lang":"fr","type":"article","venue":"Documentation et bibliothèques","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bibliothèque et Archives nationales du Québec","funders":"","keywords":"Political science; Humanities; Art","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.005080297,0.0003500461,0.0004074061,0.009957635,0.01001329,0.01289724,0.001255847,0.001043444,0.01388715],"category_scores_gemma":[0.02147642,0.0002772937,0.0003152815,0.01815636,0.003955039,0.002908879,0.002486719,0.001339533,0.002041964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05759841,"about_ca_system_score_gemma":0.1083664,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9755436,"about_ca_topic_score_gemma":0.9770834,"domain_scores_codex":[0.994231,0.0007145604,0.0002879977,0.0004827128,0.003286716,0.0009969905],"domain_scores_gemma":[0.9685952,0.005216043,0.001389532,0.001336733,0.02110635,0.002356145],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005374271,0.0001451695,0.05273115,0.002077975,0.00008750395,0.002307172,0.1729736,0.001367954,0.008686806,0.09766333,0.1218248,0.5395973],"study_design_scores_gemma":[0.00001707518,0.00003816551,0.0583635,0.001235541,0.00005744925,0.0003676922,0.06018675,0.0003268732,0.002846675,0.001245483,0.8752285,0.00008629403],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.438319,0.02738291,0.007579914,0.04651142,0.001353445,0.0003384778,0.01449618,0.001002823,0.4630159],"genre_scores_gemma":[0.7912963,0.01905683,0.007438993,0.001766254,0.0002455356,0.0001254617,0.004398467,0.0003451227,0.175327],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9871027,"threshold_uncertainty_score":0.4179077,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0853478812996848,"score_gpt":0.3389642100144444,"score_spread":0.2536163287147596,"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."}}