{"id":"W2184973236","doi":"10.32920/ryerson.14649708","title":"Mixing Characteristics of External Loop Airlift Bioreactor using Electrical Resistance Tomography","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Fluid Dynamics and Mixing","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Airlift; Distributor; Mixing (physics); Bioreactor; Materials science; Sparging; Superficial velocity; Mechanics; Flow (mathematics); Volumetric flow rate; Mechanical engineering; Engineering; Chemistry; 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":[0.0005619565,0.0005160485,0.0003564641,0.000388947,0.0001434719,0.0006045164,0.0003661463,0.0004956217,0.0006010655],"category_scores_gemma":[0.0008971384,0.0001635519,0.0003172885,0.0002990105,0.0003276827,0.0008316233,0.0004178028,0.0003816399,0.0002027088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002632639,"about_ca_system_score_gemma":0.0001966842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004555807,"about_ca_topic_score_gemma":0.0004092792,"domain_scores_codex":[0.9996137,0.00006038225,0.00002610897,0.0001097057,0.0001642188,0.00002599504],"domain_scores_gemma":[0.9994554,0.0001924222,0.0001613641,0.00003893555,0.000126513,0.00002542766],"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":[0.0001548618,0.0000329944,0.001856432,0.00008406064,0.000005411571,0.00008121852,0.00007402326,0.001544142,0.9833322,0.00009364014,0.00003997134,0.01270119],"study_design_scores_gemma":[0.000009469596,0.0002697211,0.004638181,0.000007201375,0.00002291418,0.0001619109,0.00005842153,0.03839237,0.9556798,0.0000766732,0.0006594302,0.00002388208],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8606573,0.0007322757,0.1369898,0.00009109738,0.00002628664,0.0000421262,0.0001606497,0.0005014085,0.0007991331],"genre_scores_gemma":[0.9500027,0.0004364813,0.04818999,0.0000416099,0.00001241898,0.00003388479,0.0001893136,0.0000618465,0.001031651],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006045164,"threshold_uncertainty_score":0.002971947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01031046014363888,"score_gpt":0.2155559024460532,"score_spread":0.2052454423024143,"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."}}