{"id":"W3130511535","doi":"10.1007/s11069-021-04583-2","title":"Flood risk mapping using uncertainty propagation analysis on a peak discharge: case study of the Mille Iles River in Quebec","year":2021,"lang":"en","type":"article","venue":"Natural Hazards","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Montreal Police Service; École de Technologie Supérieure","funders":"Hydro-Québec; Compute Canada","keywords":"Flood myth; Riemann solver; Hydrology (agriculture); Shallow water equations; Natural hazard; Environmental science; Latin hypercube sampling; Finite volume method; Flooding (psychology); Geology; Meteorology; Statistics; Geography; Monte Carlo method; Mathematics; Geotechnical engineering; Physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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":[0.0005548259,0.0003419264,0.0002793228,0.0009935593,0.0008222308,0.001268518,0.0006839412,0.000438879,0.001092478],"category_scores_gemma":[0.001560171,0.0001716159,0.000306397,0.001645711,0.0003693672,0.0004269685,0.0003966943,0.0003760103,0.00007491592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00668914,"about_ca_system_score_gemma":0.003935355,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9235281,"about_ca_topic_score_gemma":0.940931,"domain_scores_codex":[0.9998419,0.00004224485,0.000006664902,0.00002678343,0.00003809337,0.00004423104],"domain_scores_gemma":[0.9991755,0.0004060215,0.00005854621,0.00003990122,0.0002656919,0.00005422577],"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":[0.0002327926,0.0002007548,0.1739785,0.00009061966,0.0001474167,0.001639342,0.000937015,0.744804,0.004055191,0.00270383,0.002923198,0.06828737],"study_design_scores_gemma":[0.00001743256,0.00003205091,0.1016233,0.00001565326,0.0000320736,0.00005680388,0.0009547069,0.8953773,0.0006322314,0.0004673968,0.0007591879,0.00003192306],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910177,0.00006996446,0.005276547,0.0002004275,0.000002827444,0.00003139968,0.0007563378,0.0001251359,0.002519668],"genre_scores_gemma":[0.9952174,0.00004648751,0.003564165,0.000007688634,0.000001553899,0.000006001819,0.0002413589,0.0000125256,0.0009027947],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07647192,"threshold_uncertainty_score":0.1538445,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01077295132718211,"score_gpt":0.2588599175622152,"score_spread":0.248086966235033,"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."}}