{"id":"W837802140","doi":"10.1139/l10-056","title":"Uncertainty analysis in flood hazard assessment: hydrological and hydraulic calibrationThis article is one of a selection of papers published in this Special Issue on Hydrotechnical Engineering.","year":2010,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Flood myth; Hazard; Hydraulic engineering; Environmental science; Uncertainty analysis; Flood risk assessment; Calibration; Computer science; Uncertainty quantification; Hazard analysis; Hydrology (agriculture); Statistics; Reliability engineering; Geotechnical engineering; Geology; Risk assessment; Engineering; Mathematics; Simulation; Machine learning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.007019798,0.0009582932,0.001030051,0.001765131,0.0005232984,0.001888155,0.0007868028,0.001260774,0.001362931],"category_scores_gemma":[0.02902044,0.00055988,0.001158672,0.001626248,0.001914205,0.002880884,0.002450656,0.001883658,0.0001637121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001216369,"about_ca_system_score_gemma":0.001420969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003236901,"about_ca_topic_score_gemma":0.001979746,"domain_scores_codex":[0.9957268,0.002494656,0.000132009,0.0002822327,0.001231618,0.0001326835],"domain_scores_gemma":[0.9885495,0.009518172,0.0007236173,0.0003944288,0.000739138,0.00007513547],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003097262,0.00004530232,0.001984046,0.0002419311,0.0001500744,0.0001093441,0.0001504174,0.8249038,0.001643908,0.0759996,0.001140205,0.09360053],"study_design_scores_gemma":[0.00000691644,0.00005020805,0.002160494,0.0001059456,0.00004810232,0.0001073043,0.00007777746,0.8300811,0.002205585,0.1624303,0.002647021,0.00007920808],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01535016,0.002326865,0.9775393,0.0009381928,0.00008587205,0.00004950153,0.00007245524,0.00007158161,0.003565971],"genre_scores_gemma":[0.82376,0.007764833,0.1627081,0.0004227135,0.0009141249,0.0002484388,0.000269522,0.000163145,0.00374911],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007019798,"threshold_uncertainty_score":0.03712469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004604748182748346,"score_gpt":0.1895906290724569,"score_spread":0.1849858808897086,"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."}}