{"id":"W2114327727","doi":"10.1061/(asce)hy.1943-7900.0000187","title":"Sensitivity of Field Data Estimates in One-Dimensional Hydraulic Modeling of Channels","year":2010,"lang":"en","type":"article","venue":"Journal of Hydraulic Engineering","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"University of Waterloo","keywords":"Sampling (signal processing); Discretization; Channel (broadcasting); Sensitivity (control systems); Range (aeronautics); Field (mathematics); Hydrology (agriculture); Environmental science; Floodplain; Computer science; Geology; Engineering; Geotechnical engineering; Mathematics; Geography; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005022058,0.0005442639,0.0005218586,0.0007983446,0.0005034579,0.0009962949,0.0009033056,0.0007937276,0.0003523648],"category_scores_gemma":[0.03320146,0.0004725845,0.0003760657,0.0009052223,0.0008151333,0.001326809,0.0006439353,0.0006011838,0.00006892976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0027173,"about_ca_system_score_gemma":0.001129573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1015603,"about_ca_topic_score_gemma":0.06125939,"domain_scores_codex":[0.9976708,0.0009919706,0.0001938698,0.0005353881,0.000471883,0.0001360246],"domain_scores_gemma":[0.9624219,0.02956424,0.001984599,0.002964178,0.002775652,0.0002894653],"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":[0.000149164,0.0001651605,0.06665522,0.0000421805,0.00006516603,0.00005680463,0.0001089092,0.9238849,0.001082662,0.0004223198,0.0001816197,0.007185934],"study_design_scores_gemma":[0.00005809735,0.000166076,0.04911238,0.00002624678,0.00004054843,0.00006566306,0.0001678707,0.9436916,0.005207018,0.000941073,0.0004657862,0.00005784183],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9904926,0.0000901593,0.007988373,0.00008431378,0.000009001012,0.0000411471,0.0005298679,0.000152866,0.0006116414],"genre_scores_gemma":[0.9967895,0.00003262751,0.002571185,0.00001376309,0.000002453609,0.00001378057,0.0005033303,0.000007801116,0.00006547973],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1015603,"threshold_uncertainty_score":0.2019382,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01994508765809304,"score_gpt":0.2336729574708595,"score_spread":0.2137278698127665,"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."}}