{"id":"W3168275446","doi":"10.3390/w13091248","title":"Understanding Uncertainty in Probabilistic Floodplain Mapping in the Time of Climate Change","year":2021,"lang":"en","type":"article","venue":"Water","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Global Water Futures; University of Saskatchewan","keywords":"Floodplain; Flood myth; Climate change; Environmental science; Probabilistic logic; Watershed; Hydrology (agriculture); Flash flood; Computer science; Environmental resource management; Geography; Geology; Machine learning; Artificial intelligence; Cartography","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":[0.002984789,0.0004418302,0.0004672753,0.001793689,0.0004561022,0.001883994,0.0007914414,0.0005667412,0.0007889543],"category_scores_gemma":[0.009682856,0.0004082118,0.0007415617,0.001595517,0.0008190981,0.002315556,0.001320492,0.0006123083,0.00005392108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001656856,"about_ca_system_score_gemma":0.001704506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02007048,"about_ca_topic_score_gemma":0.01698261,"domain_scores_codex":[0.9993278,0.000333841,0.0000330054,0.0001056197,0.0001371218,0.00006265517],"domain_scores_gemma":[0.9970951,0.002188471,0.0003369978,0.0001034184,0.0002135186,0.00006259125],"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":[0.00001012653,0.000008150179,0.003211316,0.00001544922,0.00002880443,0.00005661021,0.0001103929,0.9671268,0.0002341032,0.01946927,0.0001129015,0.009616104],"study_design_scores_gemma":[0.000001700316,0.000009707822,0.001954389,0.000007795568,0.00001066688,0.00002282795,0.00006848422,0.9767188,0.0001565134,0.02053785,0.0005006814,0.00001055063],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1268051,0.0001776531,0.8689325,0.000364488,0.00001018595,0.00004867932,0.0003842676,0.0001930458,0.003084069],"genre_scores_gemma":[0.8922815,0.0002001951,0.106774,0.00001986556,0.00001626613,0.00006918023,0.0002025858,0.000039862,0.0003965735],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02007048,"threshold_uncertainty_score":0.03990728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05869422510329024,"score_gpt":0.2303771186533989,"score_spread":0.1716828935501087,"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."}}