{"id":"W3188335606","doi":"","title":"An Unusual Cold February 2019 in Saskatchewan—A Case Study Using NCEP Reanalysis Datasets","year":2019,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Climatology; Environmental science; Meteorology; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002072621,0.0002678551,0.0003321895,0.0001021513,0.0002204496,0.0001023588,0.0003513717,0.000117493,0.00002606646],"category_scores_gemma":[0.0001141112,0.0002740929,0.0000607006,0.0004487348,0.0000712952,0.0005061044,0.000222301,0.0003774035,0.0003854898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000261661,"about_ca_system_score_gemma":0.00002933237,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5380419,"about_ca_topic_score_gemma":0.1066963,"domain_scores_codex":[0.9972686,0.0002698544,0.0006341915,0.0007260308,0.0005444639,0.0005568801],"domain_scores_gemma":[0.9984932,0.0002319226,0.0002983701,0.0007517735,0.00001139506,0.0002133414],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001619078,0.0006228685,0.8684117,0.00001171566,0.00002223736,0.001659507,0.002907063,0.1206495,0.004134198,1.44819e-7,0.000330309,0.001234591],"study_design_scores_gemma":[0.001645054,0.0007156935,0.8910623,0.0002268874,0.0001998535,0.0005917661,0.08280499,0.01937069,0.001784321,0.00001605095,0.0002974537,0.001284943],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987928,0.00001428473,0.000004783144,0.00001261593,0.0001733366,0.0003490802,0.00033275,0.00006641957,0.000253876],"genre_scores_gemma":[0.9981407,8.214407e-7,0.001298422,0.00004312872,0.00009064181,0.000005683858,0.0003485045,0.00002668571,0.00004539271],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4313456,"threshold_uncertainty_score":0.9999712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02900889866854972,"score_gpt":0.2950267989243696,"score_spread":0.2660179002558198,"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."}}