{"id":"W4407140708","doi":"10.3390/hydrology12020025","title":"Coupling HEC-RAS and AI for River Morphodynamics Assessment Under Changing Flow Regimes: Enhancing Disaster Preparedness for the Ottawa River","year":2025,"lang":"en","type":"article","venue":"Hydrology","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto and Region Conservation Authority; Université Laval; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Beach morphodynamics; Preparedness; Hydrology (agriculture); Flow (mathematics); Geology; Environmental science; Geotechnical engineering; Sediment transport; Geomorphology; Sediment; Mechanics; Physics; Management","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005674284,0.0001886299,0.0002114122,0.00007173856,0.0004422852,0.00004820634,0.000237908,0.00008981104,0.00007207537],"category_scores_gemma":[0.00001683952,0.0001437198,0.00007854053,0.0001420018,0.0002491416,0.0001627202,0.000408044,0.0001038522,0.000006995975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002417379,"about_ca_system_score_gemma":0.00002155372,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001536463,"about_ca_topic_score_gemma":0.0008142319,"domain_scores_codex":[0.998675,0.00002803719,0.0002283791,0.0004666043,0.0001305727,0.0004714389],"domain_scores_gemma":[0.9991953,0.0003579005,0.00008797401,0.0003046085,0.000012625,0.00004160502],"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":[0.0002707302,0.0003321899,0.021182,0.0003206118,0.0007379717,0.000007362021,0.00858649,0.8959239,0.003723954,0.03421931,0.02070113,0.01399442],"study_design_scores_gemma":[0.000944193,0.0001027179,0.003866064,0.0000216215,0.0001853541,0.00000169137,0.0008153887,0.9673915,0.00009114652,0.0054083,0.02098911,0.0001828986],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2773814,0.00009972844,0.7174033,0.002534105,0.0005550075,0.001213618,0.00001051613,0.00004003423,0.0007623415],"genre_scores_gemma":[0.9785678,0.00006077264,0.01414456,0.002221847,0.000072473,0.000581537,0.00002854357,0.00002385301,0.0042986],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7032587,"threshold_uncertainty_score":0.5860724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007151167302525023,"score_gpt":0.2736243876857636,"score_spread":0.2664732203832386,"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."}}