{"id":"W3026711075","doi":"10.3390/atmos11050538","title":"Predictability of the Strong Ural blocking Event in January 2012 in the Subseasonal to Seasonal Models of Europe and Canada","year":2020,"lang":"en","type":"article","venue":"Atmosphere","topic":"Climate variability and models","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Predictability; Advection; Climatology; Vorticity; Environmental science; Potential vorticity; Geostrophic wind; Event (particle physics); Positive vorticity advection; Atmospheric sciences; Meteorology; Vortex; Geology; Mathematics; Geography; Physics; Thermodynamics","routes":{"ca_aff":false,"ca_fund":false,"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":[0.0004914128,0.0007693905,0.000508652,0.0005384989,0.0009157119,0.001308028,0.001141045,0.0007284699,0.001244095],"category_scores_gemma":[0.001256547,0.0003714192,0.001047397,0.0006598935,0.0005517293,0.0004205916,0.0005382439,0.0006303864,0.0001479434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005949326,"about_ca_system_score_gemma":0.006223607,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9203441,"about_ca_topic_score_gemma":0.8058801,"domain_scores_codex":[0.9998215,0.00002039591,0.000008712346,0.00005245925,0.00003012384,0.00006680411],"domain_scores_gemma":[0.9994715,0.00007263608,0.00005712554,0.00003337207,0.0002271886,0.0001381873],"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":[0.0001402908,0.00006275777,0.08823124,0.00002671958,0.0002091267,0.0001488197,0.00006815976,0.9035207,0.001292538,0.001286026,0.002669111,0.002344598],"study_design_scores_gemma":[0.00003812119,0.00001038851,0.03506241,0.000007083362,0.0000342051,0.00001516187,0.00004255643,0.9636384,0.0002596786,0.0001867247,0.0006803294,0.00002497361],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943067,0.0002001384,0.0007290024,0.0003067836,0.00003413717,0.00001278697,0.001470281,0.0001531148,0.002787024],"genre_scores_gemma":[0.9978186,0.00008782887,0.0002909534,0.0000292281,0.00000780279,0.000006166308,0.001128578,0.00002600602,0.0006047534],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07965589,"threshold_uncertainty_score":0.1602499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01583591850062325,"score_gpt":0.2063781503089665,"score_spread":0.1905422318083432,"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."}}