{"id":"W4402017025","doi":"10.5194/gmd-17-6365-2024","title":"Impact of ITCZ width on global climate: ITCZ-MIP","year":2024,"lang":"en","type":"article","venue":"Geoscientific model development","topic":"Climate variability and models","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Biological and Environmental Research; Natural Sciences and Engineering Research Council of Canada; Climate Program Office; Directorate for Geosciences; Sight Research UK; Alfred P. Sloan Foundation; Natural Environment Research Council; Met Office; National Science Foundation","keywords":"Intertropical Convergence Zone; Climatology; Environmental science; Climate model; Tropics; Equator; Atmospheric sciences; Climate change; Meteorology; Geology; Geography; Precipitation; Oceanography; Latitude; Geodesy","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001038295,0.0002701269,0.0002384142,0.00008192429,0.0002200013,0.0001336766,0.0003884289,0.0001027061,0.001887876],"category_scores_gemma":[0.00002650253,0.000216827,0.0001799563,0.0006318559,0.0002216427,0.000239136,0.000434023,0.0001293726,0.001518097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00109335,"about_ca_system_score_gemma":0.0002193165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002082515,"about_ca_topic_score_gemma":0.00009135881,"domain_scores_codex":[0.9971747,0.00003694334,0.0005107303,0.000867719,0.0007507182,0.0006592381],"domain_scores_gemma":[0.9991563,0.00003850281,0.00006668313,0.0005135086,0.00001907173,0.0002059641],"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":[0.0001889749,0.001439172,0.04890404,0.0003435683,0.0001395063,0.0000361192,0.004406233,0.8273026,0.01147225,0.01078748,0.0313726,0.06360746],"study_design_scores_gemma":[0.0003106529,0.0001060292,0.0542658,0.0001660415,0.00002869551,0.0000118226,0.00002916153,0.9302009,0.0008710414,0.00740796,0.006039045,0.0005628206],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.964714,0.00003628842,0.01277352,0.00008547819,0.0007301642,0.000331086,0.0003071169,0.0001345982,0.02088775],"genre_scores_gemma":[0.9905512,0.00001867275,0.007778048,0.00005762827,0.00001323518,0.00003328891,0.00006540267,0.00001700301,0.001465577],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1028983,"threshold_uncertainty_score":0.9992594,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02397820300466351,"score_gpt":0.2845036742102644,"score_spread":0.2605254712056009,"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."}}