{"id":"W2955840681","doi":"10.1039/c9ra02784j","title":"Fly ash based robust biocatalyst generation: a sustainable strategy towards enhanced green biosurfactant production and waste utilization","year":2019,"lang":"en","type":"article","venue":"RSC Advances","topic":"Microbial bioremediation and biosurfactants","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Biotechnology Research Institute; McGill University; Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Fisheries and Oceans Canada; Canada Foundation for Innovation","keywords":"Sustainable production; Production (economics); Waste management; Environmental science; Pulp and paper industry; Chemistry; Biochemical engineering; Engineering; Economics","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":[0.0001442606,0.0005194618,0.0002513535,0.0002315197,0.0001221659,0.0003185874,0.0002658196,0.0005104508,0.0003628575],"category_scores_gemma":[0.0001068015,0.0001053916,0.0002570297,0.0002202738,0.0001688777,0.0003417966,0.0002832372,0.0003285721,0.0002480505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002980801,"about_ca_system_score_gemma":0.0002020726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006435832,"about_ca_topic_score_gemma":0.001691489,"domain_scores_codex":[0.9998901,0.00001390973,0.00001137491,0.00002447075,0.00004108098,0.00001906046],"domain_scores_gemma":[0.9999614,0.000004951703,0.000009787249,0.000005222395,0.00001022601,0.000008455695],"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":[0.00001864343,0.00001006564,0.00005452924,0.00003633016,0.000003126065,0.00004224895,0.000003965496,0.0001134945,0.9976548,0.00007260376,0.0000235165,0.001966642],"study_design_scores_gemma":[0.000002444496,0.00004751507,0.0003913636,0.000002988753,0.00000464233,0.00006490113,0.000006587116,0.001081927,0.9975086,0.00003715145,0.0008482347,0.000003465028],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9574767,0.004156346,0.03420718,0.0002909324,0.0000709814,0.00008690878,0.0005437272,0.0002494481,0.002917725],"genre_scores_gemma":[0.9834529,0.001373956,0.01276397,0.00004636623,0.00000751747,0.00002475026,0.0002980038,0.00001906452,0.002013556],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006435832,"threshold_uncertainty_score":0.002162755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02103076081517872,"score_gpt":0.2363461901487348,"score_spread":0.215315429333556,"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."}}