{"id":"W2768082481","doi":"10.1007/s11269-017-1851-y","title":"Concept of Equivalent Reliability for Estimating the Design Flood under Non-stationary Conditions","year":2017,"lang":"en","type":"article","venue":"Water Resources Management","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":46,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada","funders":"Fundamental Research Funds for the Central Universities; China Postdoctoral Science Foundation; Central University Basic Research Fund of China; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Flood myth; Reliability (semiconductor); Engineering design process; Series (stratigraphy); Computer science; Return period; Hydrogeology; Probabilistic design; Estimation; Mathematical optimization; Reliability engineering; Environmental science; Mathematics; Engineering; Geology; Systems engineering; Geotechnical engineering","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":[0.004916218,0.001205836,0.001044474,0.00184279,0.0003068413,0.0012939,0.001425152,0.00114,0.001370701],"category_scores_gemma":[0.02308563,0.000512265,0.0009127816,0.000777119,0.001555048,0.002515174,0.001156324,0.00104993,0.0002942448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007459636,"about_ca_system_score_gemma":0.0006200298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001359616,"about_ca_topic_score_gemma":0.000644498,"domain_scores_codex":[0.9976563,0.001187116,0.0001119087,0.0003869934,0.0005391288,0.0001184658],"domain_scores_gemma":[0.9867225,0.01009431,0.0006882709,0.001058592,0.001305011,0.0001312381],"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":[0.0001065214,0.00004257881,0.002255731,0.0001244739,0.0001196167,0.000108674,0.0001454792,0.8509329,0.005289892,0.08083973,0.0006067827,0.05942757],"study_design_scores_gemma":[0.00000408261,0.00005055985,0.0005171284,0.00001377024,0.00002860421,0.00007707802,0.00001190816,0.9729325,0.001153681,0.02474826,0.0004477627,0.00001461603],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003965734,0.00007927069,0.9955564,0.0000173922,0.000007593178,0.000005331977,0.00001455607,0.00005021008,0.0003035009],"genre_scores_gemma":[0.7185118,0.0005690064,0.2788313,0.00009998891,0.0001987995,0.0001740792,0.0001882064,0.0001350104,0.00129192],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004916218,"threshold_uncertainty_score":0.02599978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02287102261824604,"score_gpt":0.2737777592540066,"score_spread":0.2509067366357606,"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."}}