{"id":"W4250986252","doi":"10.1007/s00382-012-1387-z","title":"Climate simulation over CORDEX Africa domain using the fifth-generation Canadian Regional Climate Model (CRCM5)","year":2012,"lang":"en","type":"article","venue":"Climate Dynamics","topic":"Climate variability and models","field":"Environmental Science","cited_by":103,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Canada Research Chairs; Canadian Foundation for Climate and Atmospheric Sciences; Ministère du Développement Économique, de l’Innovation et de l’Exportation","keywords":"Climatology; Precipitation; Equator; Hadley cell; Climate model; Diurnal cycle; Monsoon; Environmental science; Magnitude (astronomy); Intertropical Convergence Zone; Walker circulation; Atmospheric sciences; Climate change; Geology; General Circulation Model; Sea surface temperature; Geography; Meteorology; Latitude; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002796489,0.0006869756,0.0005122369,0.0004460379,0.0008529022,0.0006818982,0.00115798,0.0007329251,0.006252641],"category_scores_gemma":[0.0008271501,0.0002227362,0.0004207928,0.0007049967,0.00034322,0.0003297372,0.0004269223,0.0005870048,0.0003683245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005012814,"about_ca_system_score_gemma":0.004817091,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.8317603,"about_ca_topic_score_gemma":0.7658175,"domain_scores_codex":[0.9998677,0.00002539696,0.000005117625,0.00003264255,0.00002509478,0.00004403507],"domain_scores_gemma":[0.9996527,0.00005638575,0.00002131343,0.00001753885,0.0001886993,0.0000633817],"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":[0.000492181,0.000172655,0.02866775,0.0001637453,0.0001182991,0.0004548758,0.0001402617,0.9426898,0.001766786,0.003835229,0.01171638,0.009782119],"study_design_scores_gemma":[0.0002961518,0.00004530219,0.01861964,0.00002609793,0.00004025588,0.00003935404,0.0001192882,0.9711449,0.0009718901,0.0003226984,0.00833856,0.0000358076],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9418488,0.0006537837,0.003084682,0.0007682922,0.0001725091,0.0001652758,0.01840267,0.0008775633,0.03402646],"genre_scores_gemma":[0.9805009,0.0002316304,0.006005636,0.0001514288,0.00002554956,0.0001011286,0.00746741,0.00006719502,0.005449105],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8317603,"threshold_uncertainty_score":0.338461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0577697285325624,"score_gpt":0.2773694771974188,"score_spread":0.2195997486648564,"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."}}