{"id":"W4386927685","doi":"10.7202/1091508ar","title":"LES CHANGEMENTS CLIMATIQUES ET LE NIVEAU DE PRÉPARATION DES PROVINCES CANADIENNES ET DU YUKON POUR LIMITER LES DOMMAGES POTENTIELS DUS AUX INONDATIONS","year":2016,"lang":"fr","type":"article","venue":"Assurances et gestion des risques","topic":"Soil erosion and sediment transport","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Political science; Geography; Forestry","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":[],"consensus_categories":[],"category_scores_codex":[0.0008195786,0.0003501305,0.0002694984,0.001115525,0.0008615075,0.001393401,0.0005010572,0.0004083023,0.003847903],"category_scores_gemma":[0.002278912,0.0001427323,0.0004221323,0.001957747,0.0005748018,0.0005284935,0.001242193,0.0005237614,0.0002961886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007260856,"about_ca_system_score_gemma":0.01585981,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5805506,"about_ca_topic_score_gemma":0.7412823,"domain_scores_codex":[0.9993912,0.0001018234,0.00003416633,0.00009322343,0.0001678078,0.0002117439],"domain_scores_gemma":[0.9988261,0.0001546767,0.0002241487,0.0000736904,0.0005169749,0.0002043716],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008257205,0.0001202527,0.7534778,0.0008448513,0.0004194604,0.0004042897,0.001706705,0.03038277,0.01303035,0.01299603,0.008282525,0.1775093],"study_design_scores_gemma":[0.00003485716,0.0001042735,0.9626025,0.0001270533,0.0001148602,0.00006999495,0.001852359,0.003819376,0.002283901,0.001252694,0.0276904,0.00004782089],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9419547,0.006469756,0.007068046,0.003764666,0.0001318112,0.0001472149,0.00416276,0.0002157332,0.03608536],"genre_scores_gemma":[0.9892673,0.001245971,0.002963392,0.00009956227,0.000007304398,0.00003892565,0.0009246561,0.00002070909,0.005432226],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4194494,"threshold_uncertainty_score":0.8438392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06851573232969205,"score_gpt":0.290518029750854,"score_spread":0.222002297421162,"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."}}