{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007369838,0.0004169998,0.0004809797,0.001447325,0.002122909,0.002013638,0.0009866176,0.002009701,0.001667581],"category_scores_gemma":[0.001449235,0.0002860882,0.0004946127,0.003539544,0.0008812815,0.0007021427,0.001262696,0.000949882,0.0002932241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006619486,"about_ca_system_score_gemma":0.006892696,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7555503,"about_ca_topic_score_gemma":0.8759562,"domain_scores_codex":[0.9996386,0.00004311417,0.00002928881,0.0000672015,0.00008087277,0.0001408363],"domain_scores_gemma":[0.9990808,0.0001242432,0.0001624333,0.0000776183,0.0002998738,0.000254951],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006493732,0.0002673848,0.8860526,0.0002885916,0.0005900769,0.03098275,0.003314528,0.01933087,0.005473459,0.001630389,0.03632993,0.01509],"study_design_scores_gemma":[0.00005375617,0.00005433177,0.9492807,0.0001293194,0.0001133353,0.001504341,0.01961757,0.01239614,0.0008730179,0.0006710573,0.01521549,0.00009093759],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9832141,0.0003107329,0.0004971373,0.001997195,0.0001320569,0.00006701543,0.007769589,0.00009646558,0.005915625],"genre_scores_gemma":[0.9941292,0.0002528512,0.0004201707,0.000469181,0.00004066918,0.00003307022,0.003031973,0.00002696076,0.001595982],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2444497,"threshold_uncertainty_score":0.4917786,"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."}}