{"id":"W1903582008","doi":"10.14796/jwmm.r236-18","title":"Low-Flow Modification of Flood Control Channels in Cities","year":2010,"lang":"en","type":"article","venue":"Journal of Water Management Modeling","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Hong Kong Polytechnic University","keywords":"Flood control; Flow (mathematics); Environmental science; Flood myth; Control (management); Hydrology (agriculture); Geography; Geology; Computer science; Geotechnical engineering; Mechanics; Archaeology; Physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0002410351,0.0001976389,0.0001634254,0.0002804173,0.0004207234,0.001107799,0.0003767285,0.000231221,0.00218426],"category_scores_gemma":[0.0006800299,0.00015803,0.0001858954,0.0003221944,0.0008147993,0.0004174777,0.0005826275,0.0002208406,0.0001646872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009215855,"about_ca_system_score_gemma":0.001161441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01123986,"about_ca_topic_score_gemma":0.02905264,"domain_scores_codex":[0.9998026,0.00005213812,0.000009089983,0.00003693358,0.00003930044,0.00005993368],"domain_scores_gemma":[0.9997067,0.00006490001,0.00006799511,0.00004467772,0.00005961533,0.00005601869],"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":[0.0003620558,0.0004497561,0.1205941,0.0001172734,0.00004077878,0.000648855,0.000747059,0.7643508,0.0243898,0.01174769,0.001173374,0.07537844],"study_design_scores_gemma":[0.0001015629,0.0007299886,0.1733606,0.00005052422,0.00008902424,0.0002762129,0.001807456,0.7916864,0.01638581,0.005364463,0.01004559,0.00010225],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9674086,0.00004210444,0.02254815,0.00004721719,0.000008320972,0.00007900276,0.00008149131,0.0001890901,0.009596142],"genre_scores_gemma":[0.9951608,0.00003187575,0.003338696,0.000007671286,0.000001170524,0.00001736198,0.00002803432,0.000008570687,0.001405741],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01123986,"threshold_uncertainty_score":0.02234888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01114260233281132,"score_gpt":0.2237167132138347,"score_spread":0.2125741108810233,"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."}}