{"id":"W2024414272","doi":"10.1175/bams-d-11-00263.1","title":"Use of NWP for Nowcasting Convective Precipitation: Recent Progress and Challenges","year":2013,"lang":"en","type":"article","venue":"Bulletin of the American Meteorological Society","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":585,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; McGill University","funders":"National Center for Atmospheric Research; National Science Foundation","keywords":"Nowcasting; Numerical weather prediction; Meteorology; Extrapolation; Environmental science; Data assimilation; Radar; Climatology; Convective storm detection; Storm; Computer science; Geography; Geology; Mathematics; Telecommunications","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":[0.01642974,0.001127852,0.001899084,0.001431521,0.0007197569,0.00377504,0.003327812,0.001506466,0.001911643],"category_scores_gemma":[0.01665898,0.000748698,0.0007322214,0.003845299,0.002024561,0.007620669,0.002939918,0.004557868,0.001363269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001146007,"about_ca_system_score_gemma":0.003103097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0147537,"about_ca_topic_score_gemma":0.01044701,"domain_scores_codex":[0.996798,0.001077314,0.0003484067,0.0003778881,0.001280422,0.0001180982],"domain_scores_gemma":[0.987272,0.003772569,0.0008018765,0.001250865,0.006334147,0.0005686107],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001889257,0.0001263758,0.007561653,0.00331623,0.0001360493,0.0001352957,0.0004292011,0.02220078,0.005069687,0.02188419,0.01966297,0.9192888],"study_design_scores_gemma":[0.0001421796,0.000239213,0.01238769,0.00337732,0.0001900297,0.000285689,0.001205095,0.1451109,0.007877699,0.03671795,0.7922012,0.0002649585],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.05482828,0.4782563,0.3295709,0.07259507,0.01075208,0.000543819,0.002637506,0.002922958,0.0478931],"genre_scores_gemma":[0.152917,0.4538163,0.3754224,0.002291841,0.005394143,0.0003667746,0.003477846,0.001412731,0.004900858],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01642974,"threshold_uncertainty_score":0.0868898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07866047793073937,"score_gpt":0.2512894676983971,"score_spread":0.1726289897676577,"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."}}