{"id":"W4412590550","doi":"10.1016/b978-0-443-33631-7.00004-4","title":"Prediagnosis of flooding using real-time monitoring of climate parameters","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Hydrological Forecasting Using AI","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph; University of Ottawa; Université Laval","funders":"","keywords":"Flooding (psychology); Environmental science; Meteorology; Geography; Psychology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000419887,0.0003671268,0.0007481046,0.0001159147,0.00009672806,0.00001497459,0.000390307,0.0003446154,0.0003414738],"category_scores_gemma":[0.0000821154,0.0003536817,0.0002755107,0.00004048515,0.0004226961,0.00004759165,0.0005760501,0.0002951491,0.00005573381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002181618,"about_ca_system_score_gemma":0.00002467772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001923585,"about_ca_topic_score_gemma":0.000002219533,"domain_scores_codex":[0.9978659,0.00004660661,0.0007402075,0.0005121283,0.0004504661,0.00038473],"domain_scores_gemma":[0.9985298,0.0002515885,0.0005973682,0.0005049366,0.00002150844,0.00009481279],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004333353,0.00004088273,0.006241549,0.0004513215,0.0001813267,0.00003054244,0.0003522139,0.008690912,0.02308654,0.0001351463,0.00003391061,0.9607123],"study_design_scores_gemma":[0.006781664,0.004825211,0.006732201,0.1018323,0.01253524,0.0002069893,0.0001235097,0.05766354,0.4269615,0.05570974,0.310922,0.01570609],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.2632088,0.0000486556,0.000002089766,0.000004865427,0.0002122394,0.000287521,0.00004194864,0.00004829591,0.7361456],"genre_scores_gemma":[0.1388889,0.0009453796,0.06782032,0.00006878411,0.0002579231,0.00004228179,0.0000225631,0.000242493,0.7917113],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9450063,"threshold_uncertainty_score":0.9998915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02603914385857216,"score_gpt":0.2542911736212434,"score_spread":0.2282520297626713,"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."}}