{"id":"W1968483358","doi":"10.1002/aic.13858","title":"Numerical investigation of the hydrodynamics of split‐and‐recombination and multilamination microreactors","year":2012,"lang":"en","type":"article","venue":"AIChE Journal","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Consejo Nacional de Ciencia y Tecnología","keywords":"Microreactor; Residence time distribution; Mixing (physics); Flow (mathematics); Mechanics; Homogeneous; Convection; Diffusion; Distribution (mathematics); Manifold (fluid mechanics); Intensity (physics); Chemistry; Materials science; Physics; Thermodynamics; Optics; Mechanical engineering; Mathematics; Engineering","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":[0.0004151827,0.00006281646,0.00008575959,0.00008361223,0.00003397945,0.000005970528,0.00004894623,0.00005747454,0.000003021676],"category_scores_gemma":[0.00004861694,0.00004832297,0.00001700888,0.0002188502,0.0000788895,0.0002025055,0.00001632555,0.0001575377,1.752033e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004926101,"about_ca_system_score_gemma":0.000009586701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003779098,"about_ca_topic_score_gemma":7.351986e-8,"domain_scores_codex":[0.9995083,0.00002181688,0.0002572306,0.00003548481,0.00009701285,0.00008016694],"domain_scores_gemma":[0.9996426,0.00002566521,0.0001412415,0.0000590359,0.0001113578,0.000020088],"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":[0.000003583534,0.00001812491,0.06795501,0.0000720043,0.00002552684,5.671692e-8,0.001491559,0.00001669247,0.9034582,0.008918558,0.0003007696,0.01773994],"study_design_scores_gemma":[0.0001794187,0.00002219932,0.3503697,0.00004840969,0.00001740561,0.00004670239,0.00009725803,0.006281181,0.6416708,0.0010198,0.00017782,0.00006931349],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9703881,0.0002261601,0.02889542,0.00007296921,0.0001647811,0.00006411879,0.00000185291,0.0000144117,0.0001721627],"genre_scores_gemma":[0.9983709,0.00004441279,0.001514235,0.00001521825,0.00003106317,0.000001155117,0.000004809494,0.000008647909,0.000009597815],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2824146,"threshold_uncertainty_score":0.1970554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007429083820966974,"score_gpt":0.2069638455101731,"score_spread":0.1995347616892061,"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."}}