{"id":"W2349164969","doi":"","title":"A 0～6 h Quantitative Snow(Rain) Forecast Technique and Its Application in Vancouver Winter Olympics","year":2013,"lang":"en","type":"article","venue":"Guangdong Meteorology","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nowcasting; Quantitative precipitation forecast; Snow; Meteorology; Environmental science; Mesoscale meteorology; Precipitation; Radar; Rain and snow mixed; Climatology; Extrapolation; Freezing rain; Numerical weather prediction; Computer science; Geography; Geology; Mathematics","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":[0.0003269307,0.0004152655,0.0001845124,0.0005213333,0.00036254,0.000319544,0.0004473306,0.0001887598,0.0005412145],"category_scores_gemma":[0.0004963129,0.0001702507,0.0001399277,0.0006607717,0.0001071491,0.0002175237,0.0002708025,0.0002760036,0.0001106103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000536981,"about_ca_system_score_gemma":0.0009399859,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.315921,"about_ca_topic_score_gemma":0.399223,"domain_scores_codex":[0.9998631,0.00002747785,0.000006220929,0.00003759164,0.00004576518,0.00001978658],"domain_scores_gemma":[0.9998305,0.00002201843,0.00001173332,0.00001483473,0.00008803198,0.00003285207],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007604637,0.0002783427,0.2342272,0.0002784337,0.0001032002,0.0008657699,0.0007548077,0.2820023,0.07552138,0.001099437,0.004574254,0.3995345],"study_design_scores_gemma":[0.0001101925,0.0001457175,0.1839416,0.00002146598,0.00003829971,0.00008697638,0.0003750976,0.7989072,0.01164216,0.0002385248,0.00444337,0.00004949379],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9604107,0.0001795622,0.03000263,0.000176793,0.00004052889,0.0001123206,0.0015157,0.0007716015,0.006790148],"genre_scores_gemma":[0.979905,0.0001291924,0.01791433,0.00001213638,0.000008685513,0.00001919068,0.0007776731,0.00002557578,0.001208267],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.684079,"threshold_uncertainty_score":0.6281643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02238624441256814,"score_gpt":0.2394672272512124,"score_spread":0.2170809828386443,"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."}}