{"id":"W4236664950","doi":"10.32920/ryerson.14665599","title":"Using tomography, CFD, and dynamic tests to study the continuous-flow mixing of yield-pseudoplastic fluids","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Shear thinning; Computational fluid dynamics; Mixing (physics); Rheology; Mechanics; Materials science; Yield (engineering); Flow (mathematics); Fluid dynamics; Mechanical engineering; Engineering; Composite material; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008091404,0.0005033379,0.0003433144,0.0009699622,0.0002275164,0.0005889082,0.0003385504,0.0005734037,0.0004892129],"category_scores_gemma":[0.001433893,0.0002540234,0.0003351593,0.0006926024,0.0005510655,0.001178739,0.0005299086,0.000415638,0.0001029145],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003476919,"about_ca_system_score_gemma":0.000445074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007102987,"about_ca_topic_score_gemma":0.0008020813,"domain_scores_codex":[0.9995984,0.00007786535,0.00003232935,0.00006162788,0.0002022387,0.00002758118],"domain_scores_gemma":[0.9993248,0.0003361842,0.0001588177,0.00005259601,0.000105268,0.00002238761],"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":[0.000244014,0.0001238063,0.009254218,0.0003699071,0.00003196524,0.0002640336,0.0001701507,0.02324284,0.9030657,0.002455005,0.0001225362,0.06065569],"study_design_scores_gemma":[0.00002957496,0.0006293301,0.009371312,0.00003823862,0.00005221029,0.0004592949,0.0001433178,0.2439462,0.7414922,0.0008753896,0.002893872,0.00006907242],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6993128,0.002203502,0.2947617,0.0001575195,0.00005040453,0.0001418196,0.0001551944,0.0004248831,0.002792085],"genre_scores_gemma":[0.8912635,0.001022316,0.1066275,0.00004217947,0.00001650183,0.00009474772,0.0001065105,0.00003633622,0.0007903875],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009699622,"threshold_uncertainty_score":0.004279137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03232299842512208,"score_gpt":0.3015622714415628,"score_spread":0.2692392730164407,"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."}}