{"id":"W3126410816","doi":"10.1061/(asce)he.1943-5584.0002079","title":"Comparing Five Kinematic Wave Schemes for Open-Channel Routing for Wide-Tooth-Comb-Wave Hydrographs","year":2021,"lang":"en","type":"article","venue":"Journal of Hydrologic Engineering","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Jubilee Hospital","funders":"","keywords":"Hydrograph; Kinematic wave; Routing (electronic design automation); Channel (broadcasting); Geology; Kinematics; Open-channel flow; Flow routing; Hydrology (agriculture); Computer science; Meteorology; Computer network; Surface runoff; Geotechnical engineering; Drainage basin; Geography; Physics; Cartography; Turbulence","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0009116852,0.0001829631,0.0004833556,0.0001719851,0.0001574885,0.0001459052,0.0002914719,0.00007919782,0.00005614452],"category_scores_gemma":[0.0006572577,0.0001516379,0.0002374761,0.0001842624,0.0000285658,0.000354683,0.00004291231,0.0002453784,0.000001782767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001278962,"about_ca_system_score_gemma":0.00004823977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005146344,"about_ca_topic_score_gemma":0.000004044681,"domain_scores_codex":[0.9986922,0.00002908982,0.0005378971,0.0001952068,0.0001728136,0.0003728656],"domain_scores_gemma":[0.9986154,0.0006476483,0.0003176572,0.0001413313,0.0001635853,0.0001143057],"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":[0.0005456196,0.0002536217,0.03749035,0.001365311,0.001128155,0.0006549932,0.002062892,0.8955667,0.004042696,0.001250559,0.02326423,0.03237487],"study_design_scores_gemma":[0.0007916426,0.0003086959,0.0006596457,0.0002380417,0.0000597855,0.0002982621,0.0002352784,0.9824127,0.00677814,0.00256635,0.005444237,0.0002072096],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7102957,0.003490838,0.2810897,0.001707298,0.001330549,0.0006838814,0.00002885709,0.0001572484,0.001216013],"genre_scores_gemma":[0.9309679,0.00006567516,0.06811941,0.0005928241,0.0001445998,0.000004085758,0.00002125402,0.000009346606,0.00007495511],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2206722,"threshold_uncertainty_score":0.6183616,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04263059418904608,"score_gpt":0.2380039608828117,"score_spread":0.1953733666937656,"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."}}