{"id":"W4400006633","doi":"10.1007/s00449-024-03051-y","title":"Enhanced low-cost lipopeptide biosurfactant production by Bacillus velezensis from residual glycerin","year":2024,"lang":"en","type":"article","venue":"Bioprocess and Biosystems Engineering","topic":"Microbial bioremediation and biosurfactants","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Canada Foundation for Innovation","keywords":"Surfactin; Industrial and production engineering; Bioremediation; Aeration; Chemistry; Bioreactor; Bioprocess; Substrate (aquarium); Central composite design; Lipopeptide; Chromatography; Food science; Response surface methodology; Pulp and paper industry; Bacteria; Chemical engineering; Bacillus subtilis; Biology; Organic chemistry","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":[0.0001491088,0.00046774,0.0002962851,0.0002260166,0.0001117505,0.0005201592,0.0002260847,0.0002214673,0.0004157521],"category_scores_gemma":[0.0001821586,0.0001123966,0.0003232836,0.00023431,0.000151444,0.0003433419,0.0004540488,0.0004559572,0.0003195772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002180698,"about_ca_system_score_gemma":0.000244966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001283939,"about_ca_topic_score_gemma":0.001314674,"domain_scores_codex":[0.9998446,0.00002342832,0.00001449617,0.00002304742,0.00005429459,0.00004008979],"domain_scores_gemma":[0.9999464,0.000009285296,0.0000128083,0.000006522364,0.00001172561,0.00001345394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000517489,0.00001829681,0.0001012178,0.00001740559,0.000003005278,0.00004292287,0.000009432609,0.0001036697,0.9985257,0.00003196572,0.000009043833,0.001085551],"study_design_scores_gemma":[0.000003887828,0.00005807209,0.000705099,0.000002801291,0.000007097362,0.00005353822,0.00001932467,0.0005324915,0.9982972,0.00001124954,0.0003057505,0.000003553457],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948401,0.0003256245,0.003775061,0.00007432057,0.00001471195,0.0000143825,0.0001541582,0.00005335893,0.0007481581],"genre_scores_gemma":[0.9955368,0.0002215179,0.002226882,0.00001333709,0.000002923219,0.000009878529,0.0004131834,0.00002413172,0.001551285],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001283939,"threshold_uncertainty_score":0.002552927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004456275856658905,"score_gpt":0.1817914612511411,"score_spread":0.1773351853944822,"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."}}