{"id":"W3130413094","doi":"10.1002/cjce.24084","title":"Extraction and concentration of glutathione from yeast by membranes","year":2021,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lallemand (Canada); University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Lallemand","keywords":"Ultrafiltration (renal); Glutathione; Membrane; Nanofiltration; Chemistry; Extraction (chemistry); Chromatography; Yeast; Permeation; Biochemistry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0003201511,0.0004276857,0.0003787577,0.0002864278,0.0002381504,0.0002686508,0.0002573664,0.000303556,0.0003619784],"category_scores_gemma":[0.000217661,0.0001401512,0.0002935096,0.0003178886,0.0001428193,0.0003375283,0.0002629145,0.0004115053,0.0002435382],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000269149,"about_ca_system_score_gemma":0.0003213998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001136352,"about_ca_topic_score_gemma":0.001946385,"domain_scores_codex":[0.9998251,0.00003624553,0.0000181713,0.00004303886,0.00005328068,0.00002432881],"domain_scores_gemma":[0.9999348,0.00001263246,0.00001076136,0.00001041736,0.00002498923,0.00000639274],"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":[0.00001718581,0.000007004771,0.00007475284,0.00006268336,0.000005121614,0.000013561,0.00001546299,0.00006283119,0.9974421,0.00007253763,0.00001574903,0.002211009],"study_design_scores_gemma":[0.000002400084,0.00006382449,0.000338652,0.000005562861,0.000006592549,0.00003620532,0.00001125165,0.000245593,0.9978524,0.00003009027,0.001404482,0.000002938548],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9177015,0.007948635,0.07129074,0.0002107407,0.00008872588,0.0001827361,0.0004216449,0.000211812,0.00194352],"genre_scores_gemma":[0.9285594,0.005722294,0.06013719,0.00008315077,0.00002378101,0.0001300468,0.0007684419,0.0000498736,0.004525794],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001136352,"threshold_uncertainty_score":0.002259493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006052138991405921,"score_gpt":0.1870692953667342,"score_spread":0.1810171563753283,"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."}}