{"id":"W2052821867","doi":"10.1016/j.vaccine.2009.06.058","title":"A methodological approach to scaling up fermentation and primary recovery processes to the manufacturing scale for vaccine production","year":2009,"lang":"en","type":"article","venue":"Vaccine","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"Sanofi (Canada)","funders":"Sanofi Pasteur","keywords":"SCALE-UP; Cross-flow filtration; Fermentation; Process engineering; Biochemical engineering; Filtration (mathematics); Scaling; Mass transfer; Production (economics); Pulp and paper industry; Environmental science; Chemistry; Chromatography; Engineering; Food science; Mathematics; Biochemistry; Physics; Membrane","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006416689,0.0001283397,0.0001645252,0.0000621924,0.0001916124,0.00004755381,0.0001788792,0.00005482019,0.00003175599],"category_scores_gemma":[0.0004643569,0.00008481762,0.00002142196,0.0003004555,0.000005469668,0.0002285897,0.0001012733,0.00007417623,0.00002468056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008550546,"about_ca_system_score_gemma":0.00000546447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009750761,"about_ca_topic_score_gemma":0.00001470656,"domain_scores_codex":[0.9989504,0.00004848411,0.000205585,0.0004431678,0.0001511804,0.0002011804],"domain_scores_gemma":[0.9995692,0.00007442761,0.00006355636,0.0002247506,0.00001404498,0.00005396588],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001144087,0.000240884,0.002597199,0.0001972682,0.00001742931,5.061241e-7,0.001772102,0.0388254,0.378292,0.00004024995,0.02161553,0.5552573],"study_design_scores_gemma":[0.0005172408,0.0004503052,0.306385,0.0000247752,0.00002853722,0.00002694313,0.0004167898,0.0003010341,0.6842993,0.002260966,0.005024447,0.0002646577],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9437595,0.00004197497,0.04516909,0.008930847,0.00009943078,0.001423717,0.000002358609,0.0001421112,0.0004309542],"genre_scores_gemma":[0.8885801,0.0000501361,0.1085293,0.001522299,0.0001079831,0.0002218082,0.00001735707,0.00001050766,0.000960525],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5549927,"threshold_uncertainty_score":0.3458762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06173825634579401,"score_gpt":0.3054054897036305,"score_spread":0.2436672333578365,"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."}}