{"id":"W2416278938","doi":"10.1002/2016gl067862","title":"Austral winter external and internal atmospheric variability between 1980 and 2014","year":2016,"lang":"en","type":"article","venue":"Geophysical Research Letters","topic":"Climate variability and models","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Bundesministerium für Bildung und Forschung","keywords":"Empirical orthogonal functions; Predictability; Climatology; Southern Hemisphere; Atmospheric circulation; Monsoon; Northern Hemisphere; Mode (computer interface); Environmental science; Sea surface temperature; Atmospheric dynamics; Atmospheric research; Atmospheric sciences; Geology; Geography; Atmosphere (unit); Meteorology","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":[0.0002182851,0.0002139555,0.0001482026,0.0006359057,0.0001942704,0.0005097448,0.00012283,0.0001628963,0.001002213],"category_scores_gemma":[0.0005988942,0.00008886957,0.0002310181,0.0007166584,0.0001949099,0.0003192782,0.0004499491,0.0002362275,0.0001995787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005590165,"about_ca_system_score_gemma":0.0003051048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04452059,"about_ca_topic_score_gemma":0.07364351,"domain_scores_codex":[0.99993,0.000007362224,0.000006066752,0.00002266553,0.00001637384,0.00001759296],"domain_scores_gemma":[0.9996432,0.00002638006,0.0001501298,0.00002385122,0.00009745568,0.00005893638],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001311777,0.00003248536,0.9801605,0.00004630395,0.0001539467,0.00012747,0.0003635122,0.002806328,0.002511111,0.0003012831,0.002182133,0.01118374],"study_design_scores_gemma":[0.000002192126,0.000009165072,0.9979785,0.000005062224,0.00001000267,0.00002031739,0.00006308052,0.0008693828,0.0001009742,0.00003663107,0.0009022059,0.000002550406],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965407,0.00007010309,0.0001037349,0.00005302792,0.00001337759,0.00000242879,0.001986631,0.00001777974,0.001212078],"genre_scores_gemma":[0.9967744,0.00006351612,0.0000886507,0.00001106732,0.00001641643,0.00000430807,0.002362764,0.000006955967,0.0006719572],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04452059,"threshold_uncertainty_score":0.08852291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03119427568487064,"score_gpt":0.3036387696341715,"score_spread":0.2724444939493009,"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."}}