{"id":"W2971199049","doi":"10.1029/2019ms001726","title":"The GFDL Global Ocean and Sea Ice Model OM4.0: Model Description and Simulation Features","year":2019,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":490,"is_retracted":false,"has_abstract":true,"ca_institutions":"Pacific Institute for Climate Solutions; University of Victoria; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; National Oceanic and Atmospheric Administration; National Science Foundation","keywords":"Sea ice; Climate model; Environmental science; General Circulation Model; Climate simulation; Climatology; Geology; Meteorology; Oceanography; Climate change; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006814032,0.0001199073,0.0002117695,0.00004846916,0.0001533275,0.000130473,0.0001183425,0.00006325515,0.000001214106],"category_scores_gemma":[0.00004338895,0.00007810982,0.00003530034,0.00008461618,0.00004669829,0.0009826449,0.00001218152,0.0002165485,0.000001277413],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001175827,"about_ca_system_score_gemma":0.00005634342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001300051,"about_ca_topic_score_gemma":0.0002818711,"domain_scores_codex":[0.9988685,0.00005376879,0.0004061644,0.000144934,0.0003236908,0.0002029297],"domain_scores_gemma":[0.9993444,0.0001313642,0.0002390975,0.00009581682,0.0001091884,0.00008011023],"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":[0.00009368122,0.000004039109,0.07312426,0.00004200232,0.000006579633,0.000001748071,0.0001767814,0.9208882,0.000002220712,0.0002778315,0.000002630704,0.005380015],"study_design_scores_gemma":[0.0003160834,0.00007892333,0.002482991,0.0001365433,0.0000126905,0.00007988153,0.0007312347,0.9911685,1.445963e-7,0.004843988,0.0000539904,0.00009501574],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8149958,0.007387156,0.176575,0.00006140892,0.0003716726,0.0001295311,0.0000150403,0.000006566523,0.0004577784],"genre_scores_gemma":[0.9932789,0.002757775,0.003772319,0.00004133478,0.00008564892,1.100581e-7,0.000003387119,0.000003471325,0.00005710251],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.178283,"threshold_uncertainty_score":0.3185226,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01171477910421587,"score_gpt":0.2401119824079808,"score_spread":0.228397203303765,"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."}}