{"id":"W2043006903","doi":"10.1175/2008mwr2448.1","title":"Quantification of the Lateral Boundary Forcing of a Regional Climate Model Using an Aging Tracer","year":2008,"lang":"en","type":"article","venue":"Monthly Weather Review","topic":"Climate variability and models","field":"Environmental Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ouranos; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Foundation for Climate and Atmospheric Sciences; Université du Québec à Montréal","keywords":"Forcing (mathematics); TRACER; Environmental science; Climatology; Domain (mathematical analysis); Atmospheric circulation; Climate model; Boundary (topology); General Circulation Model; Meteorology; Variance (accounting); Atmospheric sciences; Geology; Climate change; Mathematics; Geography; Physics","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":[0.000543181,0.00009734811,0.00023007,0.00001160943,0.0001464237,0.000005039432,0.0001997364,0.00003357486,0.0001238092],"category_scores_gemma":[0.0000126178,0.00006817345,0.0001285581,0.000133958,0.0001968618,0.00024503,0.00008278407,0.00006820032,0.000004547661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005633366,"about_ca_system_score_gemma":0.00001888062,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002631646,"about_ca_topic_score_gemma":0.00005230546,"domain_scores_codex":[0.9989438,0.00009838767,0.0003761303,0.0002032762,0.0002245775,0.0001538449],"domain_scores_gemma":[0.9993059,0.00001732196,0.0002065007,0.0004255204,0.00001281412,0.00003192203],"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":[0.00006824378,0.0009672241,0.07749002,0.0037927,0.00004333364,0.000003157217,0.008216477,0.7941623,0.10445,0.0009590745,0.00038454,0.009462877],"study_design_scores_gemma":[0.0002697174,0.00003512537,0.01756694,0.002580496,0.00012709,0.00002045641,0.00003230757,0.9734502,0.001300029,0.001779411,0.002573126,0.0002651023],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99241,0.00525178,0.0008655234,0.0002599108,0.00002548035,0.000363297,0.00001844228,0.00001163583,0.0007939215],"genre_scores_gemma":[0.9934183,0.004270928,0.001945321,0.0002802741,0.000007329135,0.000009868015,0.000005289549,0.00001345889,0.00004917161],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1792879,"threshold_uncertainty_score":0.2780032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09730236066525787,"score_gpt":0.2978763401664838,"score_spread":0.200573979501226,"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."}}