{"id":"W3142004923","doi":"10.82308/34723","title":"A test for evaluating the downscaling ability of one-way nested regional climate models : the big-brother experiment","year":2002,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Climate variability and models","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Medical Research Council; Université du Québec à Montréal; U.S. Department of Energy","keywords":"Brother; Downscaling; Nested set model; Test (biology); Statistics; Computer science; Mathematics; Geography; Meteorology; Geology; Data mining; Precipitation; Political science; Law","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01375162,0.0006184463,0.0005391021,0.0004183153,0.0005045995,0.0007918744,0.001220137,0.0009956036,0.0009917675],"category_scores_gemma":[0.03675868,0.0002959151,0.001217155,0.0003897146,0.001149033,0.0020179,0.001675617,0.00147359,0.0001324039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003989883,"about_ca_system_score_gemma":0.0006258595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003797583,"about_ca_topic_score_gemma":0.002261044,"domain_scores_codex":[0.9963348,0.0021553,0.0002532711,0.0005706448,0.0005430858,0.0001430274],"domain_scores_gemma":[0.959843,0.03001591,0.002259694,0.005237112,0.001939828,0.0007043686],"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":[0.006371201,0.001565021,0.1114967,0.0004749487,0.001886821,0.0002566143,0.001151214,0.7583152,0.02446122,0.02440537,0.002661461,0.06695428],"study_design_scores_gemma":[0.0006371562,0.003714893,0.02819636,0.00006028169,0.0001680878,0.00008027955,0.000376339,0.94525,0.01321472,0.006607916,0.001602811,0.00009113346],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9384082,0.0001594895,0.05858384,0.0001846104,0.0001038459,0.0001425122,0.0004208849,0.0003527142,0.001643948],"genre_scores_gemma":[0.9706672,0.00003276877,0.02816563,0.00009065992,0.00002338299,0.0001266391,0.0006096033,0.000126593,0.0001574893],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01375162,"threshold_uncertainty_score":0.07272637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1212981689673942,"score_gpt":0.2891688340493781,"score_spread":0.1678706650819839,"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."}}