{"id":"W2032776399","doi":"10.1002/cjce.21616","title":"Characterisation of the mixing of non‐newtonian fluids with a scaba 6SRGT impeller through ert and CFD","year":2011,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Electrical and Bioimpedance Tomography","field":"Engineering","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Impeller; Computational fluid dynamics; Mixing (physics); Shear thinning; Mechanics; Rheology; Non-Newtonian fluid; Materials science; Slip factor; Agitator; Newtonian fluid; Mechanical engineering; Engineering; Physics; Composite material","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.0008175448,0.0002853805,0.0004056188,0.0006748414,0.0003126733,0.0004159176,0.0004087414,0.0004267541,0.001004887],"category_scores_gemma":[0.001362203,0.0002054609,0.0002833218,0.0005542319,0.0005124325,0.0004300398,0.0002746209,0.0003514872,0.0001798514],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004699615,"about_ca_system_score_gemma":0.0003209029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002536297,"about_ca_topic_score_gemma":0.001985916,"domain_scores_codex":[0.9996532,0.00005685887,0.00002705277,0.00004930523,0.0001818984,0.0000317479],"domain_scores_gemma":[0.9994798,0.0002361887,0.00008152841,0.0000549896,0.00012589,0.00002156663],"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":[0.0004107996,0.00006909927,0.004656155,0.0000756169,0.00001051656,0.0002692089,0.000197683,0.01070023,0.9655349,0.0004877626,0.0001188444,0.01746921],"study_design_scores_gemma":[0.00003355389,0.0003875093,0.01059317,0.000008306406,0.0000134316,0.0001999259,0.00008714428,0.1167659,0.8700065,0.00009078985,0.001785296,0.00002831239],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9614094,0.0001667455,0.03708456,0.0000575963,0.00001348978,0.000054135,0.0001505294,0.000207062,0.0008564515],"genre_scores_gemma":[0.9741216,0.0001009447,0.02478264,0.000008915852,0.000004166794,0.00002603377,0.000122109,0.00002511997,0.000808445],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002536297,"threshold_uncertainty_score":0.005043089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006542539029087448,"score_gpt":0.1517601371837406,"score_spread":0.1452175981546532,"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."}}