{"id":"W2964749973","doi":"10.1139/cjce-2018-0692","title":"Climate model bias correction for nonstationary conditions","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Climate variability and models","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Climate change; Environmental science; Climatology; Precipitation; Climate model; Statistics; Econometrics; Sample (material); Meteorology; Mathematics; Geography; Geology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.002998919,0.000597756,0.000528041,0.0009112483,0.0004084541,0.0005210558,0.0009414926,0.0004620591,0.001710226],"category_scores_gemma":[0.008831901,0.0002593152,0.0007105796,0.00117023,0.0002535874,0.0007501491,0.0006875267,0.0009796171,0.000483472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005245073,"about_ca_system_score_gemma":0.001203832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01112306,"about_ca_topic_score_gemma":0.01534425,"domain_scores_codex":[0.9990996,0.000282754,0.00006563498,0.0001949902,0.0002833181,0.00007373292],"domain_scores_gemma":[0.9970499,0.001054675,0.0003618126,0.0006455386,0.0008524929,0.00003555877],"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":[0.0004060157,0.0001965098,0.09585302,0.0004878632,0.0009651243,0.000277528,0.0006727785,0.3605687,0.03276336,0.01354233,0.01013501,0.4841318],"study_design_scores_gemma":[0.00007727685,0.00007067281,0.05351571,0.00005443731,0.0001599977,0.0001740159,0.00008478384,0.8993396,0.02272651,0.007330356,0.01637859,0.00008812745],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07848661,0.0004933752,0.9155423,0.0002107078,0.0002676386,0.00009926995,0.0006426806,0.002093495,0.002163928],"genre_scores_gemma":[0.6733434,0.0003570461,0.3201596,0.0001771072,0.00008825273,0.00019247,0.001645713,0.0006928612,0.003343482],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01112306,"threshold_uncertainty_score":0.02211666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01693052810856397,"score_gpt":0.2092765300590756,"score_spread":0.1923460019505117,"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."}}