{"id":"W4321491363","doi":"10.5194/egusphere-egu23-2379","title":"Visualizing and communicating probabilistic flood forecasts maps for decision-making","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère de l’Environnement, de la Lutte contre les changements climatiques, de la Faune et des Parcs; Université du Québec à Rimouski; Ministère des Ressources naturelles et des Forêts; Université de Sherbrooke","funders":"","keywords":"Probabilistic logic; Flood myth; Presentation (obstetrics); Computer science; Streamflow; Visualization; Scale (ratio); Environmental resource management; Operations research; Data science; Environmental science; Geography; Data mining; Mathematics; Artificial intelligence; Cartography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00736196,0.001796624,0.0005071848,0.00315892,0.00158614,0.007417026,0.001540519,0.002575182,0.02524401],"category_scores_gemma":[0.0298924,0.0005960527,0.0009901564,0.002717945,0.001591057,0.00971894,0.005054173,0.001580576,0.00363982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001231622,"about_ca_system_score_gemma":0.001290894,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002389293,"about_ca_topic_score_gemma":0.002166527,"domain_scores_codex":[0.9940892,0.00435839,0.0002706937,0.0002132549,0.0008070075,0.0002614761],"domain_scores_gemma":[0.97743,0.01853086,0.0007194243,0.001300203,0.001477394,0.0005422594],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001388335,0.000423567,0.006754708,0.005384188,0.000190269,0.002832314,0.1581174,0.05017525,0.01621794,0.1324596,0.1208936,0.5051628],"study_design_scores_gemma":[0.0002151537,0.0003687618,0.006319218,0.003213212,0.0002040672,0.001188465,0.06230682,0.07782044,0.008926465,0.1958644,0.6430778,0.0004951756],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1118336,0.003277406,0.7328044,0.01818831,0.001103646,0.001435228,0.005866651,0.01595183,0.109539],"genre_scores_gemma":[0.6215954,0.003420845,0.3591155,0.0008686802,0.0004111009,0.001642952,0.002899707,0.001234775,0.008810987],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02524401,"threshold_uncertainty_score":0.08444959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0477109293633066,"score_gpt":0.3432587587408171,"score_spread":0.2955478293775105,"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."}}