{"id":"W4389151570","doi":"10.1002/cjce.25146","title":"Optimization study of obstacles in <scp>T–T</scp> mixing channel at low Reynolds numbers","year":2023,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Microfluidic and Capillary Electrophoresis Applications","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reynolds number; Mixing (physics); Mechanics; Obstacle; Pressure drop; Materials science; Drop (telecommunication); Geometry; Physics; Mathematics; Mechanical engineering; Engineering; Turbulence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003475692,0.0003742106,0.0003794513,0.0003534251,0.0004747416,0.001099821,0.0003517238,0.0004659793,0.0009410576],"category_scores_gemma":[0.0007420686,0.000261088,0.0004132154,0.0002950488,0.0004373229,0.0005225726,0.0004015172,0.0003045216,0.0002450431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005303275,"about_ca_system_score_gemma":0.0009779182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002212601,"about_ca_topic_score_gemma":0.002138649,"domain_scores_codex":[0.999833,0.00002014138,0.000006716321,0.00003073222,0.00004369529,0.00006570008],"domain_scores_gemma":[0.9996864,0.0001268825,0.0000776167,0.0000198438,0.00005461074,0.00003474694],"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":[0.000268049,0.0001547338,0.003851863,0.0002743509,0.00004304371,0.000442377,0.00007386632,0.7968246,0.1832149,0.006685439,0.0004093957,0.007757321],"study_design_scores_gemma":[0.0000602215,0.000294299,0.001743473,0.00001747169,0.0000379847,0.00008054317,0.00008927644,0.9250734,0.07038497,0.0007108228,0.001464025,0.0000435562],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9592378,0.0003697039,0.03361797,0.0001137171,0.00003720207,0.00004985617,0.0001172902,0.0001235878,0.006333061],"genre_scores_gemma":[0.9871897,0.0001747625,0.01203166,0.00001353601,0.000002768525,0.00003305353,0.00005295446,0.00001623095,0.0004851817],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002212601,"threshold_uncertainty_score":0.004399419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00681184051256568,"score_gpt":0.1798010896452338,"score_spread":0.1729892491326681,"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."}}