{"id":"W2292950885","doi":"10.1175/mwr-d-15-0316.1","title":"Dependence of Model Energy Spectra on Vertical Resolution","year":2016,"lang":"en","type":"article","venue":"Monthly Weather Review","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Spectral line; Energy (signal processing); Resolution (logic); Environmental science; Atmospheric sciences; Meteorology; Geology; Remote sensing; Geodesy; Physics; Climatology; Computational physics; Mathematics; Computer science; Statistics; Astronomy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.00189733,0.0007832125,0.0004504869,0.0005579098,0.000334277,0.0009622231,0.0008243066,0.0007602336,0.001259479],"category_scores_gemma":[0.01053189,0.0003848026,0.0006937231,0.0004570316,0.0004557087,0.0009588804,0.0008054763,0.0007508862,0.0003201212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004349132,"about_ca_system_score_gemma":0.0002947547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002863994,"about_ca_topic_score_gemma":0.001109535,"domain_scores_codex":[0.9992421,0.0002598013,0.00008432905,0.000128011,0.0001800786,0.0001056586],"domain_scores_gemma":[0.9943635,0.003269445,0.0003163179,0.001331754,0.0005565434,0.0001623562],"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":[0.0003568052,0.000127707,0.02400029,0.00008114416,0.0001976332,0.0001664857,0.00005748793,0.9444314,0.02102724,0.001325889,0.0004718686,0.007755991],"study_design_scores_gemma":[0.00005479449,0.0001240475,0.00888458,0.00002469546,0.00003203153,0.00005797412,0.00003347805,0.9629822,0.02671884,0.0006878523,0.000366254,0.00003322177],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.970111,0.0002171577,0.02456114,0.0002237228,0.00004145614,0.00004259137,0.0008568063,0.0009150687,0.003031076],"genre_scores_gemma":[0.9958675,0.00003545301,0.003231425,0.00003734235,0.000002587575,0.00002316829,0.0004708313,0.0001758633,0.0001557706],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002863994,"threshold_uncertainty_score":0.0100342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04473309933087488,"score_gpt":0.2493973965954324,"score_spread":0.2046642972645575,"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."}}