{"id":"W3027491443","doi":"10.1016/j.ces.2020.115770","title":"Residence time distribution of passive scalars in magnetic nanofluid Poiseuille flow under uniform rotating magnetic fields","year":2020,"lang":"en","type":"article","venue":"Chemical Engineering Science","topic":"Characterization and Applications of Magnetic Nanoparticles","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mechanics; Magnetic field; Ferrofluid; Hagen–Poiseuille equation; Rotating magnetic field; Nanofluid; Residence time distribution; Convection; Residence time (fluid dynamics); Flow (mathematics); Materials science; Physics; Heat transfer","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":[0.00008610629,0.0001196864,0.000143242,0.00005441118,0.00002593155,0.00003206311,0.0003068108,0.0000537576,0.00008019702],"category_scores_gemma":[0.0002319769,0.0001302752,0.00002689539,0.0009652415,0.0001218397,0.0001514933,0.00006488434,0.0001255242,0.0000260539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005059784,"about_ca_system_score_gemma":0.00003043235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001961078,"about_ca_topic_score_gemma":1.563601e-7,"domain_scores_codex":[0.9990097,0.000003680506,0.0002867423,0.0002143848,0.0002244231,0.0002610463],"domain_scores_gemma":[0.9995621,0.00006155509,0.00002390676,0.0001641397,0.0000447637,0.0001434758],"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":[0.000002595808,0.000010279,0.00005604192,0.00004542621,6.838477e-7,9.848172e-7,0.00009020492,0.1204565,0.8751629,0.0004772212,0.00004908572,0.003648003],"study_design_scores_gemma":[0.0001417897,0.00002560447,0.00233776,0.00004400472,0.00000300435,0.000001379024,0.00001161071,0.6392074,0.3580145,0.00006491819,0.00003389625,0.0001141922],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9831421,0.0001335291,0.01562157,0.0006610563,0.00003913893,0.0001387996,0.00001270686,0.0001432184,0.0001079058],"genre_scores_gemma":[0.9951612,0.00001078471,0.004707914,0.00004486426,0.00002262667,0.00001937833,0.00001148835,0.00001221473,0.000009496345],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5187508,"threshold_uncertainty_score":0.531247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005224871821205901,"score_gpt":0.1865175766234597,"score_spread":0.1812927048022538,"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."}}