{"id":"W4382244151","doi":"10.1175/bams-d-22-0095.1","title":"P-Type Processes and Predictability: The Winter Precipitation Type Research Multiscale Experiment (WINTRE-MIX)","year":2023,"lang":"en","type":"article","venue":"Bulletin of the American Meteorological Society","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Université du Québec à Montréal; Ontario Tech University; Environment and Climate Change Canada; McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; University at Albany; Environment and Climate Change Canada; National Aeronautics and Space Administration; Canada Research Chairs; McGill University; U.S. Department of Homeland Security; National Science Foundation","keywords":"Environmental science; Snow; Drizzle; Precipitation; Graupel; Meteorology; Mesoscale meteorology; Terrain; Predictability; Radiosonde; Precipitation types; Climatology; Atmospheric sciences; Geology; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001594251,0.0003759355,0.0003428099,0.0001580183,0.0005250376,0.0005140937,0.0006694618,0.0004574786,0.001181561],"category_scores_gemma":[0.002634466,0.0001949506,0.0006224971,0.0001813863,0.0004963436,0.0004585662,0.0007874052,0.001270341,0.0002198026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001018117,"about_ca_system_score_gemma":0.0009529936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05944286,"about_ca_topic_score_gemma":0.1019526,"domain_scores_codex":[0.9995034,0.0001461009,0.00002421009,0.0001399832,0.0001072613,0.00007909678],"domain_scores_gemma":[0.998,0.0006771942,0.0003834088,0.0004081759,0.0002312691,0.0002998719],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.026169,0.02217276,0.6831086,0.0001754083,0.001831362,0.0007538063,0.001123449,0.1038151,0.09078425,0.005461705,0.02711108,0.03749347],"study_design_scores_gemma":[0.002304608,0.007465186,0.8342676,0.00001994023,0.0002121411,0.00007905844,0.0004507425,0.1373733,0.008943289,0.002051261,0.006671947,0.000160963],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966698,0.000008330866,0.0006411494,0.0001208797,0.00001959316,0.00007168433,0.001578265,0.00006005797,0.0008302373],"genre_scores_gemma":[0.9900816,0.0000179056,0.002748435,0.0002554728,0.0000441515,0.0003679686,0.005120047,0.00004021029,0.001324132],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05944286,"threshold_uncertainty_score":0.1181937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03300861257530529,"score_gpt":0.3048853824288343,"score_spread":0.271876769853529,"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."}}