{"id":"W2766510573","doi":"","title":"MODELLING DRY AND WET EXTREMES OVER THE CANADIAN PRAIRIE PROVINCES BASED ON THE DYNAMICAL DOWNSCALING AND MULTIVARIATE FREQUENCY ANALYSIS APPROACHES","year":2016,"lang":"en","type":"dissertation","venue":"University Library - University of Saskatchewan (University of Saskatchewan)","topic":"Textile materials and evaluations","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Global Institute for Water Security, University of Saskatchewan","keywords":"Downscaling; Multivariate statistics; Multivariate analysis; Environmental science; Climatology; Geography; Econometrics; Statistics; Mathematics; Meteorology; Precipitation; Geology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002044414,0.0003015007,0.0001632392,0.0003755268,0.0005327185,0.0005166912,0.0006051109,0.0001487006,0.0004897357],"category_scores_gemma":[0.00052826,0.0001755078,0.0003526019,0.0005779865,0.0002015085,0.0002097443,0.0002302666,0.0003008451,0.00003326428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003355679,"about_ca_system_score_gemma":0.004134535,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9335743,"about_ca_topic_score_gemma":0.9466974,"domain_scores_codex":[0.9998955,0.00001076511,0.000004848122,0.00002698779,0.00003457639,0.00002727338],"domain_scores_gemma":[0.99986,0.00002854346,0.00002349984,0.00001012497,0.00006382811,0.00001394014],"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":[0.00005405393,0.00003749781,0.06477592,0.00002513166,0.0001038188,0.00006111174,0.00009025521,0.906453,0.002808931,0.001205436,0.0005740265,0.02381075],"study_design_scores_gemma":[0.000008551552,0.000007814955,0.04406026,0.000002517362,0.00001715005,0.000007672465,0.00004601575,0.9546724,0.0004489303,0.0001656433,0.000549014,0.00001398794],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9766891,0.0001105143,0.01870691,0.0001059664,0.00001393761,0.00003916763,0.00125488,0.0001449459,0.002934533],"genre_scores_gemma":[0.9924379,0.00007741513,0.006479652,0.000008887127,0.000004407485,0.00001363588,0.0004425452,0.000009906906,0.0005257498],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06642568,"threshold_uncertainty_score":0.1336337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01853571393724898,"score_gpt":0.1850358612174516,"score_spread":0.1665001472802027,"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."}}