{"id":"W4411236684","doi":"10.1002/aic.18922","title":"Modeling heterogeneity in large‐scale bioreactors using the method of moments with a truncated normal distribution","year":2025,"lang":"en","type":"article","venue":"AIChE Journal","topic":"Cyclone Separators and Fluid Dynamics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Sanofi Pasteur; Sanofi","keywords":"Scale (ratio); Truncated normal distribution; Distribution (mathematics); Mathematics; Bioreactor; Method of moments (probability theory); Applied mathematics; Biological system; Mathematical analysis; Physics; Chemistry; Statistics; Biology","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":[0.0006954856,0.0005177011,0.000467564,0.0004140332,0.0002827225,0.0006558066,0.000814277,0.0008877292,0.0005333224],"category_scores_gemma":[0.001845024,0.0002825729,0.0007129171,0.000312125,0.0007042288,0.0007916428,0.0007203131,0.00074285,0.0001288167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008007407,"about_ca_system_score_gemma":0.0008646449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005911873,"about_ca_topic_score_gemma":0.002296649,"domain_scores_codex":[0.999775,0.00007628615,0.00001200555,0.00003598115,0.00006811594,0.00003255875],"domain_scores_gemma":[0.9990093,0.0006543621,0.0001396682,0.00005183142,0.00009896289,0.00004581279],"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":[0.00003561778,0.00002089164,0.0007912912,0.00002158921,0.00001227498,0.00007256506,0.00001842429,0.9845977,0.004864867,0.006170915,0.0001383265,0.003255585],"study_design_scores_gemma":[0.000002123326,0.000004522898,0.00004953753,7.653288e-7,8.070773e-7,0.000005925635,0.000002218277,0.9985952,0.0004039987,0.0008663298,0.00006625864,0.000002316245],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1037507,0.0002481164,0.8935088,0.0002514937,0.00005035116,0.00004394144,0.0001066855,0.0002562205,0.001783603],"genre_scores_gemma":[0.9294206,0.0002612731,0.06817852,0.00007290458,0.00003766654,0.00009332253,0.00009383944,0.00007681496,0.001765072],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005911873,"threshold_uncertainty_score":0.01175493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009864883983382883,"score_gpt":0.2687605636015649,"score_spread":0.258895679618182,"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."}}