{"id":"W4402546719","doi":"10.1016/j.heliyon.2024.e37758","title":"Enhancing flood risk mitigation by advanced data-driven approach","year":2024,"lang":"en","type":"article","venue":"Heliyon","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Flood myth; Risk analysis (engineering); Risk management; Engineering; Computer science; Environmental science; Data science; Geography; Business","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.001105715,0.000622836,0.0005039066,0.0008551177,0.0002010553,0.0008348106,0.0007015841,0.000538801,0.000640744],"category_scores_gemma":[0.002247248,0.0002388943,0.0005674596,0.0004803725,0.0001809653,0.001050373,0.0006684395,0.0004898121,0.0001493023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004423553,"about_ca_system_score_gemma":0.0007362741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003687923,"about_ca_topic_score_gemma":0.005782001,"domain_scores_codex":[0.9997078,0.0001090789,0.00002211226,0.00005095558,0.00008096728,0.0000291515],"domain_scores_gemma":[0.999273,0.0003545048,0.00009561516,0.00006295973,0.0001901103,0.00002374595],"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":[0.00006558262,0.0001312026,0.00488103,0.0000696639,0.00007867664,0.00008209243,0.00005236368,0.9099571,0.004828889,0.001542431,0.0005491143,0.07776199],"study_design_scores_gemma":[0.000004156062,0.00003253064,0.001026388,0.000009882293,0.00001452279,0.00001650144,0.00001967986,0.9954026,0.001590052,0.001297564,0.0005765355,0.000009634645],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2914127,0.0005984119,0.6996576,0.0008127154,0.00009522284,0.0001700744,0.0007108269,0.001397167,0.005145271],"genre_scores_gemma":[0.9403507,0.0002096778,0.05818716,0.0000679995,0.00002403907,0.00007673995,0.0004408909,0.00003430904,0.0006084616],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003687923,"threshold_uncertainty_score":0.007332921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008877406823039873,"score_gpt":0.247216883315853,"score_spread":0.2383394764928131,"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."}}