{"id":"W2467906105","doi":"10.1016/j.geomphys.2017.02.004","title":"Multiscale method, central extensions and a generalized Craik–Leibovich equation","year":2017,"lang":"en","type":"article","venue":"Journal of Geometry and Physics","topic":"Advanced Mathematical Modeling in Engineering","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"China Scholarship Council","keywords":"Mathematics; Mathematical analysis; Lie group; Euler equations; Mathematical physics; Pure mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002826804,0.00007744171,0.0001834509,0.00003133215,0.0001812435,0.0001411184,0.0002320617,0.00003061247,9.973699e-7],"category_scores_gemma":[0.0002594261,0.00006259102,0.00004163415,0.00005970244,0.00002998242,0.0006794927,0.0001306343,0.0001466882,4.792315e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009829474,"about_ca_system_score_gemma":0.0000128021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002029706,"about_ca_topic_score_gemma":1.589246e-7,"domain_scores_codex":[0.9993994,0.00002155001,0.0001927693,0.0001006058,0.0001509256,0.0001347432],"domain_scores_gemma":[0.9991758,0.0001705262,0.0002255626,0.0002249116,0.00009378931,0.0001093653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003690095,0.0002363337,0.001777602,0.0001965295,0.0001377654,0.00005761419,0.002007348,0.1676165,0.02683318,0.2582509,0.00009491292,0.5427544],"study_design_scores_gemma":[0.0004136475,0.00004880957,0.004806415,0.0000584722,0.00001694389,0.00006380864,0.0000079113,0.8843167,0.001336652,0.1087505,0.0000869462,0.00009314077],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09613205,0.0001527466,0.9032421,0.0002153996,0.0001817828,0.00002985985,6.704909e-7,0.000008770849,0.00003668481],"genre_scores_gemma":[0.4666987,0.00004933408,0.5330929,0.00002812931,0.0001122294,3.484808e-7,8.164984e-8,0.000003485022,0.00001478309],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7167001,"threshold_uncertainty_score":0.2552388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04248209689465478,"score_gpt":0.3194502367759358,"score_spread":0.276968139881281,"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."}}