{"id":"W108864171","doi":"","title":"Energy and momentum consistency in subgrid-scale parameterization for climate models","year":2009,"lang":"en","type":"dissertation","venue":"TSpace (University of Toronto)","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Meteorological and Oceanographic Society; Canadian Foundation for Climate and Atmospheric Sciences; Natural Sciences and Engineering Research Council of Canada; Zonta International Foundation","keywords":"Consistency (knowledge bases); Scale (ratio); Climate model; Energy–momentum relation; Momentum (technical analysis); Statistical physics; Climate change; Environmental science; Climatology; Econometrics; Physics; Geology; Mathematics; Geography; Mechanics; Economics; Cartography; Geometry","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":[0.003843926,0.0006163979,0.0009818909,0.0005342685,0.0006449696,0.002043421,0.001528483,0.0007979973,0.001223837],"category_scores_gemma":[0.0130249,0.0006895682,0.0008499228,0.0006895498,0.001345364,0.003237578,0.001918241,0.00225543,0.0002595636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009415039,"about_ca_system_score_gemma":0.001201756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005343363,"about_ca_topic_score_gemma":0.003224996,"domain_scores_codex":[0.9989729,0.0005576631,0.00007800393,0.0001453778,0.0001874897,0.00005860204],"domain_scores_gemma":[0.995177,0.002931665,0.0005233025,0.0008976747,0.0003797344,0.00009060185],"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":[0.00006738459,0.00004708807,0.005018564,0.00006333613,0.00008020637,0.00006807072,0.0001165721,0.9055041,0.001817162,0.0700368,0.0005074565,0.0166732],"study_design_scores_gemma":[0.000006981898,0.00001323352,0.000481952,0.000008188028,0.000006202998,0.000006774797,0.00001507959,0.9715531,0.0004504341,0.02677029,0.000676872,0.00001087106],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1370192,0.0008464268,0.8540289,0.001093861,0.0002166444,0.00009204289,0.0003360208,0.0007174446,0.005649428],"genre_scores_gemma":[0.8880646,0.000420364,0.1084062,0.0002000881,0.000117768,0.0001917151,0.0003626134,0.0006662065,0.001570472],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005343363,"threshold_uncertainty_score":0.02032882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01916304321344653,"score_gpt":0.2215995732202494,"score_spread":0.2024365300068029,"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."}}