{"id":"W2784995741","doi":"","title":"Central U.S. WRF Statistical Verification of Simulated Composite Radar","year":2018,"lang":"en","type":"article","venue":"98th American Meteorological Society Annual Meeting","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Weather Research and Forecasting Model; Meteorology; Composite number; Radar; Geology; Remote sensing; Geodesy; Climatology; Computer science; Geography; Algorithm; 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":[0.005424861,0.0003414934,0.0003457041,0.0009781516,0.001006786,0.0007944297,0.001059743,0.0006487951,0.002012719],"category_scores_gemma":[0.01072171,0.0002267725,0.0004902694,0.0007789996,0.0003769259,0.0007230114,0.0005377659,0.0005904861,0.0009930861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001326155,"about_ca_system_score_gemma":0.00303023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05119449,"about_ca_topic_score_gemma":0.07948828,"domain_scores_codex":[0.9984269,0.0003931648,0.00005779817,0.0002508797,0.0006980076,0.0001731791],"domain_scores_gemma":[0.9885156,0.002776984,0.0005998365,0.002030662,0.005749465,0.0003275563],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003572609,0.0008871263,0.1804175,0.000146606,0.0004835413,0.0005366477,0.0003887569,0.5718727,0.064708,0.008493803,0.04139693,0.1270958],"study_design_scores_gemma":[0.0005285899,0.0004159153,0.1132469,0.00003545319,0.0001188091,0.000166553,0.0001267648,0.8387712,0.03434967,0.001767279,0.01038278,0.00009015879],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9230971,0.0001612726,0.04685628,0.0006488604,0.0003060639,0.0000870125,0.01144206,0.002966115,0.01443527],"genre_scores_gemma":[0.9758477,0.00001806983,0.01798435,0.00006243565,0.00002885152,0.00003026355,0.004967836,0.000176819,0.0008837483],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05119449,"threshold_uncertainty_score":0.101793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03963600303720463,"score_gpt":0.3248442885904707,"score_spread":0.285208285553266,"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."}}