{"id":"W2969497373","doi":"10.1029/2019ea000638","title":"A Relationship Between Ural‐Siberian Blocking and Himalayan Weather Anomalies","year":2019,"lang":"en","type":"article","venue":"Earth and Space Science","topic":"Climate variability and models","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Geology; Trough (economics); Climatology; Synoptic scale meteorology; Mesoscale meteorology; Anomaly (physics); Atmospheric circulation; Peninsula; Jet stream; Precipitation; Sea level; Low-pressure area; Convergence zone; Atmospheric pressure; Oceanography; Meteorology; Geography; Jet (fluid)","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":[0.0001675009,0.0001241963,0.0001198447,0.0003086404,0.0002835131,0.0005730896,0.0001127453,0.0001225621,0.0008818132],"category_scores_gemma":[0.0006212463,0.0001158259,0.0001459932,0.0004079276,0.0001827982,0.0001863439,0.0002017178,0.0001629999,0.00008139209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003550065,"about_ca_system_score_gemma":0.0003025575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03771079,"about_ca_topic_score_gemma":0.03227436,"domain_scores_codex":[0.9999249,0.00001864463,0.000008064002,0.00001893235,0.00001193497,0.00001747063],"domain_scores_gemma":[0.9996581,0.00008515795,0.0001037794,0.00005324486,0.00004561682,0.00005401552],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000608685,0.0000222264,0.9867299,0.000007334294,0.00006566689,0.0001292081,0.0001579928,0.005645233,0.00397317,0.0002633313,0.00009705873,0.002848116],"study_design_scores_gemma":[0.000002544728,0.00001038242,0.9838208,0.000002520998,0.00001904597,0.00003483185,0.00009567708,0.01542735,0.0003684747,0.00005314759,0.0001610034,0.000004206918],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995402,0.00002148172,0.0001107454,0.00001045578,0.000001183077,8.836123e-7,0.00004591896,0.000006889936,0.000262204],"genre_scores_gemma":[0.9998332,0.00001291973,0.00005255581,0.000001799054,0.000001170461,6.44412e-7,0.00005579906,8.762255e-7,0.0000410121],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03771079,"threshold_uncertainty_score":0.07498258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01845311731024421,"score_gpt":0.2306398650764093,"score_spread":0.2121867477661651,"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."}}