{"id":"W4292122093","doi":"10.1175/waf-d-21-0208.1","title":"Forecast Dropouts in the NAVGEM Model: Characterization with Respect to Other Models, Large-Scale Indices, and Ensemble Forecasts","year":2022,"lang":"en","type":"article","venue":"Weather and Forecasting","topic":"Climate variability and models","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. Naval Research Laboratory","keywords":"Forecast skill; Geopotential height; Anomaly (physics); Climatology; Quantitative precipitation forecast; Econometrics; Northern Hemisphere; Environmental science; Ensemble forecasting; Scale (ratio); Meteorology; Statistics; Computer science; Precipitation; Mathematics; Geography; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009402666,0.0001553812,0.0001567378,0.0000584105,0.0004212584,0.00006505359,0.000155401,0.00003750374,0.0001314329],"category_scores_gemma":[0.000009710074,0.0001131098,0.00002201282,0.0002833126,0.00006022158,0.0002613367,0.0003013214,0.0001784067,0.000002917699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007238994,"about_ca_system_score_gemma":0.000008832932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002435783,"about_ca_topic_score_gemma":0.001286482,"domain_scores_codex":[0.9986635,0.00009462272,0.0002022108,0.0004056115,0.000288534,0.0003455339],"domain_scores_gemma":[0.9996008,0.00005709565,0.00007265182,0.0001939599,0.000005364905,0.00007008726],"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":[0.0009120789,0.0006201122,0.1832859,0.00008335047,0.00003138472,0.00003387333,0.1781743,0.5709653,0.01075846,0.003833792,0.000160068,0.0511413],"study_design_scores_gemma":[0.000532141,0.0001799909,0.004029439,0.00002109969,0.00001130018,0.00005881102,0.00171844,0.9887158,0.00002944282,0.003506818,0.0009937312,0.000202949],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9696763,0.00001831093,0.02188595,0.0002798778,0.00001840748,0.0004784078,0.0000684135,0.00002377894,0.007550585],"genre_scores_gemma":[0.9970252,0.000005829317,0.001846315,0.0006790469,0.00001917492,0.0001211245,0.00001706612,0.00002767284,0.0002586013],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4177505,"threshold_uncertainty_score":0.4612482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03089460330254917,"score_gpt":0.2249694243557845,"score_spread":0.1940748210532353,"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."}}