{"id":"W3123329529","doi":"10.1007/s13399-021-01275-6","title":"Yeast and bacteria co-culture-based lipid production through bioremediation of palm oil mill effluent: a statistical optimization","year":2021,"lang":"en","type":"article","venue":"Biomass Conversion and Biorefinery","topic":"Microbial Metabolic Engineering and Bioproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":36,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"Universiti Malaysia Pahang; Ministry of Higher Education, Malaysia","keywords":"Chemical oxygen demand; Pome; Bacillus cereus; Response surface methodology; Yeast; Food science; Effluent; Wastewater; Chemistry; Bioremediation; Microorganism; Bacteria; Yeast extract; Pulp and paper industry; Biology; Fermentation; Environmental science; Botany; Biochemistry; Environmental engineering; Chromatography","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":[0.0008126817,0.0004624911,0.000556254,0.0004786774,0.0002175137,0.0005474751,0.0003933524,0.0002270299,0.000451338],"category_scores_gemma":[0.0008166093,0.0001915136,0.0008030706,0.0006988032,0.000191385,0.0002333642,0.0003962419,0.0003241316,0.0001196345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005147586,"about_ca_system_score_gemma":0.0009008711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003677507,"about_ca_topic_score_gemma":0.00596366,"domain_scores_codex":[0.9997128,0.00009276292,0.00002582498,0.00005340502,0.00007892976,0.00003627106],"domain_scores_gemma":[0.9996495,0.0001855742,0.00004141987,0.0000269865,0.00007736369,0.00001908206],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002823739,0.001438002,0.01109986,0.0002966514,0.000354367,0.000136379,0.00005389427,0.5312222,0.3779491,0.001914302,0.0002730745,0.07243856],"study_design_scores_gemma":[0.00006275935,0.001162101,0.004597955,0.000004692632,0.0002293276,0.0000464821,0.0000422351,0.6883434,0.304393,0.0003303963,0.0007590169,0.00002850287],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9621285,0.0003757287,0.03631052,0.00005389438,0.000007186439,0.00005101323,0.0002002524,0.00009779238,0.0007751609],"genre_scores_gemma":[0.9808499,0.0002846029,0.0176172,0.00001042068,0.000003158437,0.00005466513,0.0003167396,0.00002200742,0.0008413132],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003677507,"threshold_uncertainty_score":0.007312238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00719433563697386,"score_gpt":0.2193522783783151,"score_spread":0.2121579427413413,"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."}}