{"id":"W3094142232","doi":"10.5194/egusphere-egu2020-13752","title":"Multivariate Bias Correction of Climate Simulations: an Intercomparison Study","year":2020,"lang":"en","type":"article","venue":"","topic":"Climate variability and models","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Univariate; Multivariate statistics; Variable (mathematics); Computer science; Climate model; Climate change; Data mining; Econometrics; Multivariate analysis; Statistics; Machine learning; Mathematics","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":[0.01168037,0.0009424185,0.0007081986,0.001902127,0.0005655079,0.001264891,0.001115927,0.001087344,0.0007652577],"category_scores_gemma":[0.02465757,0.0003183636,0.001335711,0.002166912,0.0004501268,0.001715309,0.001277957,0.0009360683,0.0001463526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001005463,"about_ca_system_score_gemma":0.001276749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009011017,"about_ca_topic_score_gemma":0.0050852,"domain_scores_codex":[0.9964607,0.001742509,0.0002562743,0.0005682542,0.0008224502,0.0001498246],"domain_scores_gemma":[0.9805902,0.01060618,0.001800643,0.002730906,0.003992566,0.0002795112],"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":[0.0008781198,0.0009709192,0.1536012,0.000575053,0.00132861,0.0003648009,0.001467187,0.5491763,0.01777039,0.01272939,0.004251977,0.2568861],"study_design_scores_gemma":[0.0001171215,0.0003813361,0.04969432,0.00009093316,0.0002674155,0.00012868,0.0002912143,0.9256587,0.01446244,0.00322257,0.005544193,0.0001410525],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7495337,0.001834953,0.2410948,0.0007205922,0.0003613554,0.0002818491,0.0005160218,0.00126904,0.004387829],"genre_scores_gemma":[0.9081889,0.0005304207,0.0894542,0.00008442852,0.0001581991,0.0001514899,0.0005572894,0.0002637789,0.0006112172],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01168037,"threshold_uncertainty_score":0.06177241,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1013593743733817,"score_gpt":0.3259442943923807,"score_spread":0.2245849200189989,"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."}}