{"id":"W4399667152","doi":"10.1021/acs.iecr.4c00679","title":"Analysis of Scale-Up and Characterization of the Volumetric Mass Transfer Coefficient for Gas Dispersion in Yield-Pseudoplastic Fluids Using a Coaxial Mixer","year":2024,"lang":"en","type":"article","venue":"Industrial & Engineering Chemistry Research","topic":"Fluid Dynamics and Mixing","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computational fluid dynamics; Mixing (physics); Impeller; Mechanics; Coaxial; Mass transfer; Rushton turbine; Shear thinning; Materials science; Dispersion (optics); Mass transfer coefficient; Mechanical engineering; Rheology; Engineering; Physics; Composite material","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":[0.0005328957,0.0001245288,0.0002618966,0.0004827579,0.00003249347,0.00004448229,0.0001458395,0.0001960681,0.0000131531],"category_scores_gemma":[0.0001896079,0.0001135483,0.0001115822,0.00258666,0.00004983514,0.00005362354,0.00003802039,0.0003818833,1.239493e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001493702,"about_ca_system_score_gemma":0.000060198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003886694,"about_ca_topic_score_gemma":0.000002690517,"domain_scores_codex":[0.998862,0.00001446518,0.0003284984,0.0001967165,0.0003159441,0.0002823513],"domain_scores_gemma":[0.9994164,0.0002844395,0.00001005003,0.000157093,0.00007624238,0.00005578908],"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":[0.00002028007,0.000009697,0.0007586837,0.0003779067,0.00009932843,9.609009e-7,0.0001108008,0.1857561,0.812282,0.00001043321,0.000003550691,0.0005702876],"study_design_scores_gemma":[0.0002100204,0.00001101773,0.0004389532,0.0002656819,0.00008720042,0.000001075303,0.00002239966,0.7099267,0.2889245,6.61995e-7,0.00003885663,0.00007287873],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9818691,0.0001537588,0.01724211,0.00001222744,0.0003225563,0.0002387506,0.0001228859,0.00002749926,0.00001108014],"genre_scores_gemma":[0.9997215,0.00003881313,0.0000212867,2.834556e-7,0.0001064016,0.00001573957,0.00002773115,0.00002869059,0.00003957048],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5241706,"threshold_uncertainty_score":0.4630366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04078246327387385,"score_gpt":0.2728571727760621,"score_spread":0.2320747095021883,"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."}}