{"id":"W2971621007","doi":"10.1175/jhm-d-18-0233.1","title":"Evaluation and Comparison of CanRCM4 and CRCM5 to Estimate Probable Maximum Precipitation over North America","year":2019,"lang":"en","type":"article","venue":"Journal of Hydrometeorology","topic":"Climate variability and models","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Pacific Institute for Climate Solutions; University of Victoria","funders":"","keywords":"Climatology; Precipitation; Environmental science; Climate Forecast System; Probabilistic logic; Scale (ratio); Climate model; Bivariate analysis; Estimation; Meteorology; Climate change; Statistics; Geography; Mathematics; Geology; Cartography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008154442,0.00007348709,0.0002658307,0.00007685542,0.00002834028,0.00000957453,0.00007495884,0.00004462495,0.0004909933],"category_scores_gemma":[0.0001360408,0.000062319,0.00002340513,0.0001296319,0.00008844209,0.0002008311,0.00008020237,0.00009057281,0.00001500767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007581832,"about_ca_system_score_gemma":0.00001911609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001283308,"about_ca_topic_score_gemma":0.0003459122,"domain_scores_codex":[0.9989522,0.0001211547,0.0003473762,0.0001407669,0.0003062834,0.0001322334],"domain_scores_gemma":[0.999379,0.00009452579,0.000302547,0.00009966384,0.00004357463,0.00008070435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000152416,0.000135549,0.8111689,0.00002852212,0.00003253008,9.328162e-7,0.00192842,0.1455648,0.02539538,0.00001591103,0.0002105788,0.0153661],"study_design_scores_gemma":[0.001038951,0.002450764,0.8526618,0.00001946074,0.000141631,0.00004684764,0.00008293407,0.1369628,0.0004133743,0.004654359,0.001400495,0.0001264933],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983504,0.00006702104,0.0004275745,0.0002987128,0.0001066344,0.0002608354,0.000003235606,0.000002507841,0.0004830833],"genre_scores_gemma":[0.9957613,0.00001528626,0.004112495,0.00007233862,0.000007655907,0.000003410433,0.000001916072,0.000004825858,0.0000207819],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04149298,"threshold_uncertainty_score":0.5376031,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0201577439647474,"score_gpt":0.3107087602357296,"score_spread":0.2905510162709822,"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."}}