{"id":"W4236185602","doi":"10.32920/ryerson.14644479.v1","title":"Computational fluid dynamics (CFD) analysis of mixing in styrene polymerization","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Continuous stirred-tank reactor; Computational fluid dynamics; Impeller; Mixing (physics); Mechanics; Materials science; Polymerization; Mechanical engineering; Thermodynamics; Polymer; Engineering; Physics; Chemical engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003207288,0.000337787,0.000626376,0.0005114934,0.0005998811,0.0005495475,0.0004031036,0.0007525893,0.001507702],"category_scores_gemma":[0.0006992668,0.0002187425,0.0005679893,0.0005194556,0.0004553341,0.0003559909,0.0003110734,0.0005231024,0.0001617203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008500986,"about_ca_system_score_gemma":0.001241157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008627216,"about_ca_topic_score_gemma":0.003157869,"domain_scores_codex":[0.9998357,0.00002619549,0.00001171282,0.00002591009,0.00006852862,0.00003196852],"domain_scores_gemma":[0.9996327,0.000229234,0.00003315184,0.0000187455,0.00006601203,0.00002013578],"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":[0.0001058744,0.0000676205,0.001519965,0.00009540131,0.00001281379,0.0001217604,0.00007045623,0.9540406,0.03204658,0.004702501,0.0002809965,0.006935469],"study_design_scores_gemma":[0.000006092315,0.00001339818,0.0003249675,0.000002292006,0.000002121712,0.0000105383,0.000005424594,0.9922735,0.006777256,0.0002359673,0.0003430394,0.00000542872],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7749588,0.0005773783,0.2082015,0.0004253682,0.0001294596,0.0001621848,0.0009850361,0.000647786,0.01391247],"genre_scores_gemma":[0.9527562,0.0002876753,0.04343674,0.00003306028,0.00001453455,0.0001177989,0.0003297764,0.00005904873,0.002965156],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008627216,"threshold_uncertainty_score":0.01715398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009695981869772169,"score_gpt":0.2422456766080394,"score_spread":0.2325496947382672,"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."}}