{"id":"W2094108290","doi":"10.1016/j.cherd.2008.08.017","title":"A mapping method based on Gaussian quadrature: Application to viscous mixing","year":2008,"lang":"en","type":"article","venue":"Process Safety and Environmental Protection","topic":"Rheology and Fluid Dynamics Studies","field":"Chemical Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Gaussian quadrature; Quadrature (astronomy); Mixing (physics); Applied mathematics; Mathematics; Computer science; Calculus (dental); Nyström method; Mathematical optimization; Mathematical analysis; Physics; Integral equation; Optics","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":[0.001553642,0.0005002688,0.000710075,0.0005111965,0.0004839438,0.0007235707,0.0009480042,0.00122787,0.001884057],"category_scores_gemma":[0.002852093,0.000363106,0.0005598608,0.0007844619,0.000575864,0.0009473066,0.001229605,0.0009743905,0.0007153651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000294032,"about_ca_system_score_gemma":0.0008909692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001880685,"about_ca_topic_score_gemma":0.0015949,"domain_scores_codex":[0.9997386,0.0001029319,0.0000138605,0.00003340692,0.00009273064,0.00001842036],"domain_scores_gemma":[0.9991004,0.0005013616,0.00004720649,0.00007848657,0.0002194842,0.00005309208],"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":[0.0003777177,0.0004102245,0.001143496,0.0003201308,0.00009236602,0.0002120535,0.0003337057,0.243211,0.0724274,0.09421792,0.003146632,0.5841074],"study_design_scores_gemma":[0.00001546185,0.00003433013,0.0001064634,0.000005075181,0.000006924959,0.00003978211,0.000006384866,0.9913935,0.00346643,0.003608862,0.001305147,0.00001154946],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004302355,0.00006549336,0.9951257,0.00003815716,0.00003533806,0.00001515527,0.000007417645,0.0001441748,0.0002662073],"genre_scores_gemma":[0.09431601,0.0002386154,0.9027615,0.00005749979,0.00005056928,0.00006771772,0.00003176727,0.000182062,0.002294252],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001884057,"threshold_uncertainty_score":0.00821656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007222981725659554,"score_gpt":0.2142804717143782,"score_spread":0.2070574899887187,"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."}}