{"id":"W4315433092","doi":"10.1088/1748-9326/acb1c8","title":"Storm surge variability and prediction from ENSO and tropical cyclones","year":2023,"lang":"en","type":"article","venue":"Environmental Research Letters","topic":"Tropical and Extratropical Cyclones Research","field":"Earth and Planetary Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Education and Child Care","funders":"National Key Research and Development Program of China; State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering; Government of Jiangsu Province; Sight Research UK; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; National Natural Science Foundation of China; Natural Environment Research Council; Met Office","keywords":"Storm surge; Tropical cyclone; Climatology; Storm; Environmental science; El Niño Southern Oscillation; Forcing (mathematics); Surge; Natural hazard; Meteorology; Geology; Geography","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":[0.0003693596,0.0002201779,0.000144106,0.0002491615,0.0001341754,0.0004009834,0.0001402662,0.0001318182,0.0008038189],"category_scores_gemma":[0.0008575819,0.0001395538,0.0002463519,0.0002315855,0.0001666939,0.0002601415,0.0002003696,0.0002072846,0.0001510719],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004489727,"about_ca_system_score_gemma":0.0004028174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05273921,"about_ca_topic_score_gemma":0.03578741,"domain_scores_codex":[0.9999281,0.00001915065,0.000005948627,0.00001805362,0.00001139625,0.00001721893],"domain_scores_gemma":[0.9995127,0.0002293508,0.00009792972,0.00003431521,0.0000685266,0.00005716904],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002833072,0.0001126742,0.8022569,0.00002441114,0.0001000735,0.0002042187,0.0001257909,0.1856187,0.002808752,0.0003667362,0.0005524507,0.007546026],"study_design_scores_gemma":[0.00001830125,0.0000718134,0.5483138,0.00000550868,0.00002018401,0.00001625653,0.0001227618,0.4503719,0.0006782099,0.0001644081,0.0002075597,0.000009383243],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988741,0.00001003829,0.000505794,0.00002288613,0.000002442691,0.000002591094,0.0002047288,0.00001727017,0.0003600236],"genre_scores_gemma":[0.9995835,0.000008029653,0.00007768566,0.000001400147,0.000001763428,9.589002e-7,0.0002310673,0.000001446107,0.00009407803],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05273921,"threshold_uncertainty_score":0.1048645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02791053555734575,"score_gpt":0.2540600698278235,"score_spread":0.2261495342704778,"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."}}