{"id":"W2156536672","doi":"10.1002/2015jd023279","title":"Future changes in autumn atmospheric river events in British Columbia, Canada, as projected by CMIP5 global climate models","year":2015,"lang":"en","type":"article","venue":"Journal of Geophysical Research Atmospheres","topic":"Climate variability and models","field":"Environmental Science","cited_by":100,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia; Pacific Institute for Climate Solutions; University of Victoria; Environment and Climate Change Canada; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; National Oceanic and Atmospheric Administration","keywords":"Coupled model intercomparison project; Precipitation; Climatology; Environmental science; Climate change; Climate model; Period (music); Atmospheric sciences; Meteorology; Geography; Oceanography; Geology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00157853,0.0001675346,0.00048251,0.000004142744,0.0001216621,0.0001230656,0.0006815421,0.0001581627,0.0006312693],"category_scores_gemma":[0.0003725313,0.000203572,0.00008193978,0.001209461,0.0002819371,0.0005878282,0.0004831633,0.0008495485,0.00003394466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002739317,"about_ca_system_score_gemma":0.0008758609,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9714223,"about_ca_topic_score_gemma":0.992596,"domain_scores_codex":[0.9952248,0.0005763328,0.0005464075,0.0004212365,0.002162547,0.001068669],"domain_scores_gemma":[0.9986289,0.0001699556,0.0001782965,0.0002578268,0.0001675099,0.0005974952],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005904878,0.002028929,0.89395,0.00007241888,0.00004819313,0.0008997113,0.0008914898,0.009794786,0.000449948,0.00007854644,0.07294128,0.0182542],"study_design_scores_gemma":[0.003482134,0.001308248,0.9075608,0.0003057487,0.00001626749,0.00009915074,0.002545774,0.03498936,0.00002114954,0.04193468,0.007206498,0.0005302001],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966124,0.0002415492,0.00001091859,0.0009181148,0.0001685872,0.0004167456,0.0000588508,0.000009399479,0.001563479],"genre_scores_gemma":[0.9980204,0.0002808922,0.0008100673,0.0001461939,0.000159436,0.00002489762,0.000005520253,0.00002046463,0.0005321766],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06573478,"threshold_uncertainty_score":0.8301427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02507631971354538,"score_gpt":0.2867493191076873,"score_spread":0.2616729993941419,"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."}}