{"id":"W2979713501","doi":"10.5194/hess-24-4601-2020","title":"An uncertainty partition approach for inferring interactive hydrologic risks","year":2020,"lang":"en","type":"article","venue":"Hydrology and earth system sciences","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"National Key Research and Development Program of China; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Copula (linguistics); Multivariate statistics; Econometrics; Computer science; Inference; Uncertainty analysis; Statistics; Factorial; Flood myth; Mathematics; Artificial intelligence; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003794818,0.001224101,0.001047169,0.003216587,0.0006656494,0.001754268,0.00152673,0.0008512232,0.003190373],"category_scores_gemma":[0.01048743,0.0006245497,0.001898489,0.00147166,0.001078408,0.002242923,0.001664555,0.00130679,0.0002381104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001313567,"about_ca_system_score_gemma":0.001547164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007488448,"about_ca_topic_score_gemma":0.004846511,"domain_scores_codex":[0.998301,0.0007437404,0.00006618507,0.0003183219,0.000386507,0.0001843269],"domain_scores_gemma":[0.9950546,0.003561461,0.0004125794,0.0002552397,0.0005910266,0.000124981],"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":[0.0001029669,0.00005236149,0.004437631,0.00009399711,0.0001971846,0.0001874177,0.0002301354,0.8660437,0.00207994,0.05891009,0.0008518606,0.06681265],"study_design_scores_gemma":[0.000004000516,0.00001706629,0.0005433362,0.000009834312,0.00001977122,0.00002313565,0.00002238739,0.9785782,0.000360856,0.02007075,0.0003368676,0.0000138953],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01451422,0.0001208951,0.9842101,0.00005960752,0.000008749334,0.00003731424,0.00008567762,0.00009851724,0.0008649451],"genre_scores_gemma":[0.6981166,0.0004380234,0.2987979,0.0001040103,0.00009715263,0.0003154797,0.0004806195,0.0001296723,0.001520662],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007488448,"threshold_uncertainty_score":0.02006918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04788105084223327,"score_gpt":0.2834139496011581,"score_spread":0.2355328987589248,"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."}}