{"id":"W4280602950","doi":"10.1007/s00382-022-06269-2","title":"The predictability study of the two flavors of ENSO in the CESM model from 1881 to 2017","year":2022,"lang":"en","type":"article","venue":"Climate Dynamics","topic":"Climate variability and models","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia","funders":"National Key Research and Development Program of China; Guangdong Key Laboratory of Fermentation and Enzyme Engineering; National Natural Science Foundation of China","keywords":"Predictability; El Niño Southern Oscillation; Climatology; Multivariate ENSO index; Environmental science; Southern oscillation; Mathematics; Geology; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001936747,0.0001217639,0.0001839406,0.00001565424,0.0004849852,0.00001776595,0.001330116,0.00002831625,0.00009068655],"category_scores_gemma":[0.00009883603,0.000068193,0.00008015941,0.0003152611,0.0002823185,0.00006811506,0.001590425,0.0002725553,0.000004644603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002712684,"about_ca_system_score_gemma":0.00001924193,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003415846,"about_ca_topic_score_gemma":0.018056,"domain_scores_codex":[0.9979742,0.000442275,0.0004455367,0.000313329,0.0005506858,0.0002740277],"domain_scores_gemma":[0.9981684,0.0004194959,0.000166429,0.001202107,0.0000105217,0.00003301833],"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":[0.00007259079,0.0007512673,0.2635784,0.000006994363,0.000008002445,6.255659e-7,0.01322966,0.7209127,0.0004462251,0.0006782208,0.00006267415,0.0002525955],"study_design_scores_gemma":[0.0003603261,0.0001162946,0.1984409,0.000004290893,0.00002640093,7.029798e-7,0.009858487,0.7858227,0.00001129506,0.005232773,0.00004381143,0.00008196622],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957376,0.000007017972,0.00008583548,0.0005839776,0.0001517042,0.0009498479,0.0005933699,0.000009892458,0.001880746],"genre_scores_gemma":[0.9996204,0.00001517425,0.00008128955,0.0001240027,0.000005342747,0.0001053613,0.00001182878,0.000009216034,0.00002733027],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06513753,"threshold_uncertainty_score":0.9998619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01845493605919098,"score_gpt":0.2609474707258264,"score_spread":0.2424925346666354,"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."}}