{"id":"W4389504600","doi":"10.1016/j.envsoft.2023.105926","title":"Real-time peak flow prediction based on signal matching","year":2023,"lang":"en","type":"article","venue":"Environmental Modelling & Software","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Prince Edward Island","funders":"","keywords":"Watershed; Flood myth; Flow (mathematics); SIGNAL (programming language); Precipitation; Environmental science; Streamflow; Flood forecasting; Matching (statistics); Event (particle physics); Computer science; Real-time computing; Hydrology (agriculture); Meteorology; Geography; Statistics; Engineering; Drainage basin; Geotechnical engineering; Mathematics; Machine learning","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":[0.0004342991,0.0005723605,0.0007671801,0.001460534,0.0002509259,0.0006155637,0.000621572,0.0005130622,0.002347075],"category_scores_gemma":[0.001345568,0.0002679847,0.0003668463,0.0009552821,0.0001456551,0.0008626464,0.0004869779,0.0004662875,0.00073349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002516847,"about_ca_system_score_gemma":0.0004552903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002414762,"about_ca_topic_score_gemma":0.002010247,"domain_scores_codex":[0.9997868,0.00002573263,0.00001154374,0.00006670815,0.00007303777,0.00003614956],"domain_scores_gemma":[0.9995785,0.0001553395,0.00005466722,0.00004084102,0.0001254836,0.00004509519],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002226821,0.0004842843,0.01294483,0.0001252729,0.0001245573,0.0002173047,0.0000873134,0.2936501,0.06259695,0.002374193,0.00397008,0.6211984],"study_design_scores_gemma":[0.00001863525,0.00005489368,0.001649711,0.000002078703,0.00001261628,0.00002920001,0.000005075618,0.9925216,0.004982708,0.0005126229,0.0002038455,0.000007071869],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2375208,0.000215143,0.7538905,0.0001215425,0.0001375611,0.00008116683,0.0004791488,0.005101357,0.002452638],"genre_scores_gemma":[0.9134163,0.00008980148,0.08457769,0.00002999065,0.00005677277,0.00003658624,0.0004543086,0.00009543396,0.00124305],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002414762,"threshold_uncertainty_score":0.007851779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009247829665881864,"score_gpt":0.200096235142802,"score_spread":0.1908484054769201,"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."}}