{"id":"W3022689702","doi":"","title":"McGill Algorithm for Precipitation nowcasting by Lagrangian Extrapolation (MAPLE) applied to the South Korean Radar Netwotk. Part 2: Real-time verification for the summer season","year":2009,"lang":"en","type":"article","venue":"34th Conference on Radar Meteorology (5-9 October 2009)","topic":"Precipitation Measurement and Analysis","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Nowcasting; Extrapolation; Maple; Meteorology; Radar; Precipitation; Algorithm; Computer science; Quantitative precipitation forecast; Climatology; Remote sensing; Environmental science; Geography; Mathematics; Geology; Statistics","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":[0.0006402465,0.0003377057,0.0003568306,0.0005579436,0.0003847539,0.0005157553,0.001126251,0.0003710682,0.005823854],"category_scores_gemma":[0.002580369,0.0002832281,0.0002409206,0.0005143625,0.0001212309,0.0006812236,0.0007862134,0.0006066626,0.001076721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000435201,"about_ca_system_score_gemma":0.001704059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04492791,"about_ca_topic_score_gemma":0.07833011,"domain_scores_codex":[0.9998342,0.00004212742,0.00001249035,0.0000315725,0.0000538104,0.0000258684],"domain_scores_gemma":[0.9995993,0.000110958,0.00002669695,0.00005703577,0.0001797966,0.00002621828],"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":[0.001051991,0.0001608217,0.008137487,0.0001649134,0.0001378225,0.0001430418,0.0001568621,0.2029759,0.01862175,0.006029548,0.0276908,0.7347291],"study_design_scores_gemma":[0.00009305006,0.00002846402,0.00169225,0.000007293404,0.00001134595,0.00001413429,0.00001736701,0.9897944,0.004738783,0.0005236953,0.003064643,0.0000144794],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08910832,0.0004048091,0.8978041,0.0002297265,0.0001736191,0.000200748,0.001492137,0.006757667,0.003828895],"genre_scores_gemma":[0.2528424,0.0001367786,0.7392249,0.0001021338,0.00003458104,0.0002463695,0.002223318,0.0008416427,0.004347976],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04492791,"threshold_uncertainty_score":0.08933276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03850023667869908,"score_gpt":0.2528466591824861,"score_spread":0.214346422503787,"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."}}