{"id":"W4387781555","doi":"10.1007/s00162-023-00674-x","title":"GPU computing of yield stress fluid flows in narrow gaps","year":2023,"lang":"en","type":"article","venue":"Theoretical and Computational Fluid Dynamics","topic":"Fluid Dynamics and Turbulent Flows","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Nonlinear system; Flow (mathematics); Lagrangian; Computational science; Algorithm; Newtonian fluid; Ideal (ethics); Approx; Computational Science and Engineering; Displacement (psychology); Mathematical optimization; Applied mathematics; Parallel computing; Mechanics; Mathematics; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000186859,0.0003866647,0.0005159436,0.000468989,0.0004819002,0.001057615,0.0005907037,0.0005515923,0.002173566],"category_scores_gemma":[0.001452434,0.0002087103,0.0002367921,0.0005901508,0.0004952888,0.0006053942,0.000620847,0.0004628647,0.0002274748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004670557,"about_ca_system_score_gemma":0.0005976272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005543978,"about_ca_topic_score_gemma":0.00750452,"domain_scores_codex":[0.9999055,0.00001972313,0.000003499738,0.00001419918,0.00003036303,0.00002670754],"domain_scores_gemma":[0.9996419,0.0001727809,0.00002313975,0.00002750124,0.00008474501,0.00004991813],"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":[0.0008656608,0.0002543713,0.007102932,0.0001670255,0.00006463131,0.0004436346,0.000420141,0.8715893,0.01881495,0.02772549,0.004659318,0.06789251],"study_design_scores_gemma":[0.00001269822,0.00001406551,0.0002448858,0.000003322731,0.000002287287,0.00001264414,0.00002705524,0.9968482,0.0009095081,0.001539084,0.0003840828,0.000002220698],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8921233,0.00049944,0.08860954,0.0003789922,0.0001504606,0.00002689141,0.0001748142,0.001046001,0.01699045],"genre_scores_gemma":[0.9761322,0.0000858386,0.02203877,0.00002927857,0.00001841937,0.00001303612,0.0001038457,0.00009420876,0.001484457],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005543978,"threshold_uncertainty_score":0.0110234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005197287985673037,"score_gpt":0.2052845546577975,"score_spread":0.2000872666721245,"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."}}