{"id":"W2681669025","doi":"10.1002/2017ms001014","title":"Implementation and calibration of a stochastic multicloud convective parameterization in the NCEP <scp>C</scp>limate <scp>F</scp>orecast <scp>S</scp>ystem (CFSv2)","year":2017,"lang":"en","type":"article","venue":"Journal of Advances in Modeling Earth Systems","topic":"Climate variability and models","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Climate Forecast System; Convection; Environmental science; Madden–Julian oscillation; Climatology; Meteorology; Robustness (evolution); Precipitation; Atmospheric sciences; Geology; Physics; Chemistry","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":[0.001653286,0.0005744242,0.0003571492,0.0003023253,0.0004729604,0.0007161102,0.001562638,0.0008112152,0.0008656791],"category_scores_gemma":[0.00298719,0.000374539,0.0004637214,0.0004303052,0.000382681,0.0007847445,0.0004963578,0.0007562123,0.0001662644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009570459,"about_ca_system_score_gemma":0.001201934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04066178,"about_ca_topic_score_gemma":0.02106311,"domain_scores_codex":[0.9996189,0.0001247702,0.00003883159,0.00008526886,0.00008399182,0.00004823534],"domain_scores_gemma":[0.9991452,0.0002806078,0.00009699009,0.0002076551,0.000218542,0.00005105489],"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":[0.0001741727,0.00025032,0.01744743,0.00004344495,0.00007401745,0.00005889491,0.00006585629,0.9640744,0.006677039,0.000850575,0.0007912396,0.009492566],"study_design_scores_gemma":[0.00009973918,0.00008414812,0.006686268,0.000006916203,0.00001673131,0.000008346941,0.00002056755,0.9869441,0.005346668,0.0001261654,0.0006392082,0.00002112845],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9782882,0.00005543618,0.01550178,0.0002467102,0.00006314411,0.0001444127,0.00156398,0.001167377,0.00296902],"genre_scores_gemma":[0.9904441,0.00001694825,0.008473159,0.00003733053,0.000007408746,0.00008392091,0.0006909255,0.0000726401,0.000173437],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04066178,"threshold_uncertainty_score":0.08085018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02965959063441011,"score_gpt":0.2974736260605726,"score_spread":0.2678140354261625,"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."}}