{"id":"W4391394518","doi":"10.2139/ssrn.4711286","title":"A Coupled Metabolic Flux/Compartmental Hydrodynamic Model for Large-Scale Aerated Bioreactors","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Micro and Nano Robotics","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Bioreactor; Aeration; Flux (metallurgy); Scale (ratio); SCALE-UP; Mechanics; Environmental science; Biological system; Biochemical engineering; Physics; Chemistry; Biology; Engineering; Classical mechanics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0006157755,0.001111275,0.002080741,0.000553954,0.0008216548,0.002120778,0.002703471,0.004128593,0.003275541],"category_scores_gemma":[0.001407115,0.0009518656,0.001727848,0.0008317014,0.001294869,0.001344899,0.001945457,0.001409484,0.0006781371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001964796,"about_ca_system_score_gemma":0.00180898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02294462,"about_ca_topic_score_gemma":0.007946801,"domain_scores_codex":[0.9996081,0.00009481957,0.00002304318,0.0001388642,0.00008088527,0.00005429194],"domain_scores_gemma":[0.9994183,0.0002646582,0.00008756707,0.00003695615,0.0001188546,0.00007363866],"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":[0.00006888559,0.00003596028,0.0003101944,0.00008249732,0.00003590812,0.0001147546,0.00003797011,0.9821481,0.004646496,0.0107531,0.0004363896,0.001329814],"study_design_scores_gemma":[0.00001322746,0.00001052104,0.0001102214,0.000003144948,0.000008984424,0.000009097789,0.000005712732,0.9978508,0.0002583985,0.001362263,0.0003587934,0.000008830048],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1594472,0.002782258,0.7983101,0.002886423,0.0006260377,0.0002511806,0.002591424,0.0008287666,0.03227669],"genre_scores_gemma":[0.9332723,0.001581318,0.0280823,0.0004166957,0.0001604133,0.0006454906,0.0009908685,0.0001881852,0.03466243],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02294462,"threshold_uncertainty_score":0.04562217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009025373429937374,"score_gpt":0.2559010259848462,"score_spread":0.2468756525549088,"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."}}