{"id":"W3040595952","doi":"10.5194/hess-2020-214","title":"Possibilistic response surfaces combining fuzzy targets and hydro-climatic uncertainty in flood vulnerability assessment","year":2020,"lang":"en","type":"article","venue":"","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Ambiguity; Flood myth; Computer science; Probabilistic logic; Fuzzy logic; Vulnerability (computing); Range (aeronautics); Sample (material); Environmental science; Artificial intelligence; Geography; Engineering","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":[0.01132052,0.001180284,0.001119708,0.004918644,0.0006298225,0.003234645,0.001297247,0.001502811,0.001400996],"category_scores_gemma":[0.02271722,0.0006266718,0.00161248,0.002841171,0.002507062,0.002880917,0.002504301,0.001596731,0.0001854343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001865379,"about_ca_system_score_gemma":0.0007152021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003721203,"about_ca_topic_score_gemma":0.0018221,"domain_scores_codex":[0.994518,0.003607395,0.0002197757,0.0003283666,0.001055873,0.0002706527],"domain_scores_gemma":[0.9816765,0.01544933,0.0008179524,0.0005786372,0.001219556,0.0002580573],"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":[0.0001637651,0.00004721264,0.00334829,0.00009831518,0.0001069483,0.0001280019,0.000306119,0.9413691,0.0009459875,0.02753744,0.0002118719,0.02573696],"study_design_scores_gemma":[0.000004899493,0.00004425013,0.001060167,0.00002064568,0.00001247779,0.00003437806,0.00009104282,0.9787594,0.0003455324,0.01937426,0.0002284531,0.00002446121],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1461284,0.0003578446,0.8496869,0.0003871758,0.00002276708,0.0001176965,0.0001300118,0.0001725184,0.002996728],"genre_scores_gemma":[0.9302485,0.0001024286,0.06902643,0.00004416958,0.00002030399,0.0001025436,0.00009510469,0.00002400478,0.000336601],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01132052,"threshold_uncertainty_score":0.05986941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01699937719234223,"score_gpt":0.2763436739967041,"score_spread":0.2593442968043618,"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."}}