{"id":"W6888880582","doi":"10.25318/3510014601-fra","title":"Taux de femmes admises pour des raisons de mauvais traitements pour 100 000 femmes adultes dans la population, un aperçu instantané","year":2019,"lang":"fr","type":"dataset","venue":"Statistics Canada Dissemination","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Population; Context (archaeology); Perspective (graphical); Research methodology","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":[],"consensus_categories":[],"category_scores_codex":[0.0009845856,0.0010124,0.001089666,0.004192783,0.0007438212,0.001445354,0.001350869,0.0008322365,0.02869932],"category_scores_gemma":[0.01013335,0.0004851163,0.00094927,0.01018514,0.0003539009,0.000643958,0.0007337225,0.001076363,0.01444187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005546523,"about_ca_system_score_gemma":0.009996907,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7834569,"about_ca_topic_score_gemma":0.8353828,"domain_scores_codex":[0.9989476,0.0001191551,0.0001518829,0.0002660493,0.000345844,0.0001696145],"domain_scores_gemma":[0.9947922,0.001317655,0.0004556686,0.0003996144,0.002783631,0.0002513582],"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":[0.0001122823,0.00001568523,0.01522115,0.0008210572,0.00008032349,0.00003063127,0.00008047638,0.0003535528,0.00006752637,0.0004294379,0.9764539,0.006334055],"study_design_scores_gemma":[0.0002285293,0.00002466983,0.1639698,0.001028633,0.0001410498,0.0001514887,0.0006730473,0.0006504175,0.0004153149,0.000748781,0.8318853,0.00008274605],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004492204,0.0001288903,0.00003522504,0.00008047357,0.00001435002,0.000005410957,0.9986088,0.00005058241,0.0006271536],"genre_scores_gemma":[0.003114581,0.0003710447,0.0003067541,0.00007848939,0.0000117651,0.00006034387,0.9939407,0.00003217121,0.002084083],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2165431,"threshold_uncertainty_score":0.4356368,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02388482049171398,"score_gpt":0.3105409224589357,"score_spread":0.2866561019672217,"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."}}