{"id":"W3130545654","doi":"10.3390/geomatics1010007","title":"Application of Multimodel Superensemble Technique on the TIGGE Suite of Operational Models","year":2021,"lang":"en","type":"article","venue":"Geomatics","topic":"Climate variability and models","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Meteorology; Geopotential height; Climatology; Predictability; Environmental science; Numerical weather prediction; Model output statistics; Downscaling; Range (aeronautics); Radiosonde; Percentile; Precipitation; Geography; Statistics; Mathematics; 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":[0.0002926912,0.00006023233,0.00009982054,0.000009783484,0.00004770673,0.000005723912,0.0001290099,0.00004858927,0.0003517033],"category_scores_gemma":[0.00004492449,0.00004498753,0.00003777893,0.0001138874,0.00008634321,0.00007185803,0.00009663834,0.00005337389,0.00002255828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003026897,"about_ca_system_score_gemma":0.00001743108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001406997,"about_ca_topic_score_gemma":0.0000346007,"domain_scores_codex":[0.9993111,0.00003959394,0.0002273218,0.0001242062,0.0002123843,0.00008540555],"domain_scores_gemma":[0.999405,0.0001378907,0.00005810427,0.0003508382,0.00002824979,0.00001996053],"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":[0.000007726362,0.0003451251,0.001540857,0.0000511543,0.000009308554,2.999187e-7,0.0008471985,0.6239445,0.3043094,0.067929,0.0002366666,0.0007787209],"study_design_scores_gemma":[0.00007859636,0.00001687389,0.0005848131,0.00001287213,0.000007143468,0.000001652691,0.00006154222,0.8735129,0.09406307,0.0315235,0.00008448843,0.00005256752],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7175099,0.000004441754,0.2759237,0.0003882463,0.00001100633,0.0003080668,0.00004184059,0.00001070771,0.005802091],"genre_scores_gemma":[0.9794851,0.00000924014,0.02021193,0.0001236751,0.000004653042,0.00005360132,0.00002168273,0.000005279468,0.00008481313],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2619752,"threshold_uncertainty_score":0.3850905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02772531547299718,"score_gpt":0.2434540875762328,"score_spread":0.2157287721032356,"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."}}