{"id":"W3200158131","doi":"10.3390/mi12091102","title":"Numerical and Experimental Validation of Mixing Efficiency in Periodic Disturbance Mixers","year":2021,"lang":"en","type":"article","venue":"Micromachines","topic":"Microfluidic and Capillary Electrophoresis Applications","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; École de Technologie Supérieure; McGill University","funders":"Khalifa University of Science, Technology and Research; Natural Sciences and Engineering Research Council of Canada; École de technologie supérieure","keywords":"Micromixer; Mixing (physics); Computer science; Process (computing); Reliability (semiconductor); Image processing; Software; Image (mathematics); Artificial intelligence; 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":[0.002388659,0.0004330332,0.000378783,0.00070796,0.0003993654,0.0006429643,0.0006511515,0.0007204709,0.001161942],"category_scores_gemma":[0.005374424,0.0001879624,0.0003523751,0.0007620281,0.0008572674,0.000441003,0.0004975712,0.000565064,0.0002414963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004896561,"about_ca_system_score_gemma":0.000424432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007317907,"about_ca_topic_score_gemma":0.0005342761,"domain_scores_codex":[0.9989196,0.0001739741,0.0001031346,0.0001679323,0.0005344014,0.0001009294],"domain_scores_gemma":[0.9974926,0.001393821,0.0002481065,0.0003826354,0.000421023,0.00006193818],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004717893,0.0004305214,0.002637402,0.0004236314,0.00003474594,0.000181887,0.0003472285,0.0532977,0.9115831,0.005538952,0.0002859403,0.02476704],"study_design_scores_gemma":[0.00004057325,0.0005031337,0.001680362,0.00001726586,0.00002193404,0.00006606743,0.00006170189,0.1920117,0.8038057,0.0005494392,0.00121235,0.00002984084],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8433799,0.0006966402,0.1498263,0.0001414542,0.0001216283,0.0001796098,0.0002338768,0.0005082747,0.004912273],"genre_scores_gemma":[0.9268897,0.0003272634,0.07139099,0.00001998242,0.00001156688,0.0001434335,0.0001367053,0.00003958543,0.001040819],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002388659,"threshold_uncertainty_score":0.01263255,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004455013877789372,"score_gpt":0.2123501498004157,"score_spread":0.2078951359226263,"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."}}