{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001062329,0.0003869901,0.0003333642,0.00008520026,0.0008483529,0.000320558,0.0003062955,0.0002988438,0.000672309],"category_scores_gemma":[0.0002583732,0.0001915239,0.0001681073,0.0002869969,0.0006389938,0.001952519,0.00005298988,0.0001985462,0.0000438221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001947896,"about_ca_system_score_gemma":0.0001261917,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05546964,"about_ca_topic_score_gemma":0.2397727,"domain_scores_codex":[0.9971089,0.0009340134,0.0005056809,0.0005311709,0.0003368234,0.0005834491],"domain_scores_gemma":[0.9983784,0.0006174837,0.000279418,0.0001103464,0.0004088604,0.0002055106],"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":[0.0001403196,0.0007843875,0.310392,0.0001927902,0.0001309802,0.00002090786,0.00464066,0.0004760693,0.03553836,0.03139042,0.009276493,0.6070166],"study_design_scores_gemma":[0.0005988086,0.0005266349,0.9473648,0.001173305,0.00008843024,0.00001842795,0.002213426,0.0007790998,0.009574282,0.0046624,0.03247207,0.0005282896],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8615522,0.002911747,0.0009136962,0.12522,0.0003575845,0.0004368494,0.0002712718,0.0002123833,0.008124264],"genre_scores_gemma":[0.9701047,0.02010483,0.001766712,0.0006503296,0.0002389154,0.0001043116,0.0002006918,0.000009826726,0.006819658],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6369728,"threshold_uncertainty_score":0.9508201,"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."}}