{"id":"W3007400702","doi":"10.1029/2019wr025436","title":"Correlation Effects? A Major but Often Neglected Component in Sensitivity and Uncertainty Analysis","year":2020,"lang":"en","type":"article","venue":"Water Resources Research","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"Global Institute for Water Security; University of Saskatchewan","funders":"Canada First Research Excellence Fund","keywords":"Variogram; Sensitivity (control systems); Markov chain Monte Carlo; Econometrics; Multivariate normal distribution; Multivariate statistics; Bayesian probability; Statistics; Variance (accounting); Monte Carlo method; Computer science; Mathematics; Mathematical optimization; Kriging; Engineering","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":[0.01987234,0.0008717652,0.001041657,0.001628903,0.000586471,0.002001345,0.001137119,0.001164998,0.001656307],"category_scores_gemma":[0.07112069,0.0007368055,0.001618336,0.00185441,0.002783554,0.0031676,0.002289378,0.002627994,0.0001237058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001263501,"about_ca_system_score_gemma":0.001603216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004503103,"about_ca_topic_score_gemma":0.003358677,"domain_scores_codex":[0.9879782,0.008372093,0.0003775079,0.00100516,0.001953968,0.000313008],"domain_scores_gemma":[0.9002718,0.08979385,0.003445715,0.004225938,0.001956233,0.0003064982],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00008218757,0.00005806523,0.01855656,0.0002968805,0.0005609916,0.0003705231,0.0003302346,0.6518523,0.001841267,0.2417402,0.001542413,0.08276846],"study_design_scores_gemma":[0.00001129281,0.00006526091,0.005643312,0.00009161527,0.00007421679,0.0001174005,0.0001057615,0.812128,0.002136365,0.1772684,0.002294397,0.00006404762],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03625333,0.000675844,0.958389,0.0009757394,0.0000522256,0.00005511453,0.00007947649,0.0001632557,0.003355891],"genre_scores_gemma":[0.904909,0.0005040066,0.09298852,0.0003132028,0.0001345179,0.0001081762,0.00008662693,0.0001568557,0.0007991137],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01987234,"threshold_uncertainty_score":0.1050962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09372949867446487,"score_gpt":0.3484313434128982,"score_spread":0.2547018447384333,"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."}}