{"id":"W2075467040","doi":"10.1021/ie901130z","title":"Study of Solid−Liquid Mixing in Agitated Tanks through Computational Fluid Dynamics Modeling","year":2010,"lang":"en","type":"article","venue":"Industrial & Engineering Chemistry Research","topic":"Fluid Dynamics and Mixing","field":"Engineering","cited_by":156,"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); Rotational speed; Mechanics; Materials science; Turbulence; Homogeneity (statistics); Agitator; Eulerian path; Mechanical engineering; CFD-DEM; Engineering; Computer science; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008930456,0.0002572598,0.0003675354,0.0002120365,0.00006899162,0.00005479363,0.0004310446,0.0003808177,0.00002667189],"category_scores_gemma":[0.0004995072,0.0003088176,0.00005992909,0.000843626,0.0000466157,0.0001721758,0.0001515875,0.00224597,0.000003373708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002662745,"about_ca_system_score_gemma":0.0001128903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001658021,"about_ca_topic_score_gemma":0.00004237772,"domain_scores_codex":[0.9976954,0.00002553837,0.0006419563,0.0003406357,0.0006368203,0.0006596229],"domain_scores_gemma":[0.9989455,0.0003031172,0.0000300065,0.0003567945,0.0002426147,0.0001220013],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002256602,0.00008164404,0.00007627974,0.00005689996,0.00003482654,0.0000247187,0.000298729,0.6636673,0.3355365,0.00007499754,0.00001992529,0.0001056731],"study_design_scores_gemma":[0.001223779,0.0000644197,0.00001778271,0.0001072048,0.000006380769,0.00001118183,0.0005603667,0.9637817,0.03388597,0.00006736029,0.00002014688,0.00025378],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964904,0.00003985332,0.001777728,0.00001804233,0.0005773787,0.000315591,0.00003850215,0.0001732815,0.0005692483],"genre_scores_gemma":[0.9992195,0.00000757902,0.0002791116,8.368712e-7,0.0002824953,0.00004348825,0.00005896385,0.00008174165,0.00002628966],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3016505,"threshold_uncertainty_score":0.9999364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06471966639202471,"score_gpt":0.3270133085141224,"score_spread":0.2622936421220977,"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."}}