{"id":"W2119355060","doi":"10.1155/2011/935034","title":"Bivariate EMD‐Based Data Adaptive Approach to the Analysis of Climate Variability","year":2011,"lang":"en","type":"article","venue":"Discrete Dynamics in Nature and Society","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Bivariate analysis; Hilbert–Huang transform; SIGNAL (programming language); Climate change; Mode (computer interface); Climatology; Environmental science; Gaussian; Mathematics; Statistics; Energy (signal processing); Computer science; Physics; Geology","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":[0.00228449,0.0006314284,0.0007556234,0.001384499,0.0003436089,0.0008515083,0.0009618909,0.0005160002,0.001152968],"category_scores_gemma":[0.007072841,0.0002914078,0.000956534,0.001768753,0.0004333053,0.0008466835,0.001177171,0.001141367,0.0003509219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003538986,"about_ca_system_score_gemma":0.0004996751,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00144636,"about_ca_topic_score_gemma":0.00133763,"domain_scores_codex":[0.9989512,0.0004892601,0.00007868287,0.0002164872,0.0002040349,0.00006037326],"domain_scores_gemma":[0.9983134,0.0009350979,0.0001356546,0.0002672343,0.0003120707,0.00003655614],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003128987,0.0001476753,0.01356902,0.0002715045,0.0004195574,0.000295925,0.0002906433,0.4012162,0.01608857,0.03763238,0.002862556,0.526893],"study_design_scores_gemma":[0.000008325504,0.0000319578,0.002161825,0.0000104759,0.00002163338,0.00007663683,0.00003972043,0.9823405,0.002515381,0.009298917,0.003473849,0.00002079827],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003062082,0.00008112164,0.9963091,0.00005069418,0.00001689889,0.00001098943,0.0001082976,0.000147232,0.0002135482],"genre_scores_gemma":[0.1880037,0.000315951,0.8093905,0.00008501743,0.0000880709,0.0001790875,0.001040488,0.0001184938,0.0007784911],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00228449,"threshold_uncertainty_score":0.01208174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01508639427621207,"score_gpt":0.2514669564973672,"score_spread":0.2363805622211551,"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."}}