{"id":"W3130402338","doi":"10.1007/s12650-020-00726-y","title":"Reduced-order representation of stratified wakes by proper orthogonal decomposition utilizing translational symmetry","year":2021,"lang":"en","type":"article","venue":"Journal of Visualization","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary; BGC Engineering (Canada)","funders":"Compute Canada; Natural Sciences and Engineering Research Council of Canada; Marine Environmental Observation Prediction and Response Network","keywords":"Order (exchange); Representation (politics); Symmetry (geometry); Decomposition; Proper orthogonal decomposition; Translational symmetry; Mathematics; Pure mathematics; Computer science; Physics; Geometry; Mechanics; Political science; Chemistry; Business","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001294196,0.00008494343,0.0001737478,0.00007511034,0.00006665606,0.00003719939,0.00004694006,0.00004088446,0.0005943847],"category_scores_gemma":[0.00001207457,0.00007793081,0.0001074044,0.0003554955,0.00002234891,0.000361698,0.000006241596,0.0001088421,9.642628e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001018186,"about_ca_system_score_gemma":0.0001188674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004413423,"about_ca_topic_score_gemma":4.578837e-7,"domain_scores_codex":[0.9988244,0.0001235156,0.0005458682,0.0001151427,0.0003053447,0.00008577493],"domain_scores_gemma":[0.9987871,0.00003730964,0.0004390716,0.00006578293,0.0006208208,0.00004990365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002692814,0.0009849495,0.01806208,0.00006264412,0.0003073304,0.000004408079,0.0006853131,0.02059685,0.840708,0.06223076,0.007442796,0.04864565],"study_design_scores_gemma":[0.002015117,0.0002004415,0.006171348,0.0002680485,0.000185858,0.00006185599,0.001375777,0.05254515,0.9288452,0.006600307,0.001417655,0.0003132403],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7700388,0.0002197152,0.2273914,0.0002592344,0.0002810285,0.00007998021,0.00001303683,0.000005991782,0.001710814],"genre_scores_gemma":[0.9979401,0.00003472861,0.001301196,0.00003119096,0.0003054793,0.000001655793,0.0002228591,0.00001102139,0.0001517903],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2279013,"threshold_uncertainty_score":0.6508096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02831900519128074,"score_gpt":0.3478939047750219,"score_spread":0.3195748995837412,"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."}}