{"id":"W2586967899","doi":"10.1007/s00382-017-3525-0","title":"KNN-based local linear regression for the analysis and simulation of low flow extremes under climatic influence","year":2017,"lang":"en","type":"article","venue":"Climate Dynamics","topic":"Climate variability and models","field":"Environmental Science","cited_by":45,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics; National Research Foundation of Korea","keywords":"Heteroscedasticity; Resampling; Nonlinear system; Statistics; Econometrics; Mathematics; Variance (accounting); Linear regression; Climatology; Geology; Physics","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":[0.001549825,0.0006104169,0.00102115,0.000537636,0.0006915072,0.0006345009,0.001670199,0.001144714,0.002418204],"category_scores_gemma":[0.005440261,0.0006420858,0.0007455247,0.0007494325,0.0007006504,0.0008129474,0.001050985,0.001613523,0.0004570002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001084146,"about_ca_system_score_gemma":0.001469232,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0722665,"about_ca_topic_score_gemma":0.05138284,"domain_scores_codex":[0.9995393,0.0002407296,0.0000261447,0.00008488084,0.00005605623,0.00005311221],"domain_scores_gemma":[0.9971625,0.002072764,0.0001672074,0.0001053628,0.0003635345,0.0001286171],"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":[0.0000227076,0.00001329197,0.0002845727,0.000006707658,0.00001430869,0.000008037176,0.00000842599,0.9962071,0.00008097877,0.0004814398,0.0001315691,0.002740783],"study_design_scores_gemma":[0.000001092125,0.000001398353,0.00001867239,3.732582e-7,6.912426e-7,4.487341e-7,9.726502e-7,0.9998221,0.00001872009,0.0001195928,0.00001533265,6.927261e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1488496,0.0003982391,0.8454036,0.0003216392,0.0001181428,0.00005983772,0.0003405098,0.002082759,0.002425747],"genre_scores_gemma":[0.8470302,0.0001457589,0.1485667,0.0001329688,0.00005890203,0.000169408,0.0005498177,0.0003100027,0.003036305],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0722665,"threshold_uncertainty_score":0.1436917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02134096564242233,"score_gpt":0.2976464806223038,"score_spread":0.2763055149798814,"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."}}