{"id":"W2784963614","doi":"10.2166/wst.2018.011","title":"Performance of a membrane bioreactor in extreme concentrations of bisphenol A","year":2018,"lang":"en","type":"article","venue":"Water Science & Technology","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"CTT Group (Canada); Centre de Recherche Industrielle du Québec; Institut National de la Recherche Scientifique","funders":"","keywords":"Chemistry; Biodegradation; Bisphenol A; Membrane bioreactor; Hydraulic retention time; Nitrification; Bioreactor; Activated sludge; Environmental chemistry; Chemical oxygen demand; Nitrifying bacteria; Heterotroph; Autotroph; Bacteria; Chromatography; Sewage treatment; Environmental engineering; Nitrogen; Organic chemistry; Biology","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0002230242,0.00006389264,0.0001070938,0.0002546804,0.00006538466,0.000004399276,0.0003722755,0.00006043427,0.0004683401],"category_scores_gemma":[0.00004664845,0.00004551047,0.00001113215,0.001068898,0.003172847,0.0001476487,0.0001714385,0.00005843767,0.00009095819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005758449,"about_ca_system_score_gemma":0.00003091363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001188757,"about_ca_topic_score_gemma":0.0001304565,"domain_scores_codex":[0.9991252,0.000006196639,0.0002108599,0.0002029956,0.0001711184,0.0002836353],"domain_scores_gemma":[0.9996682,0.000008790572,0.00006029656,0.0002105941,0.00002268663,0.00002936263],"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":[0.000007667394,0.00003380479,0.05778432,0.000003153519,5.349872e-7,4.365525e-7,0.0003299785,0.00005185755,0.940123,0.0003533189,0.000005686243,0.001306219],"study_design_scores_gemma":[0.0001392865,0.0002021039,0.0169057,0.00001500376,0.000002489045,0.000006287458,0.00003967687,0.008314463,0.9736565,0.0001626407,0.0004970519,0.00005878559],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973583,0.000003739087,0.0005911418,0.0001160149,0.0000982293,0.00008637238,0.000005020788,0.00001607301,0.001725111],"genre_scores_gemma":[0.9987405,0.000007131458,0.001196738,0.000009857014,0.000005033183,0.00000377402,5.771082e-7,0.000002428405,0.0000339733],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04087861,"threshold_uncertainty_score":0.99954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01494925969897219,"score_gpt":0.2027653397085506,"score_spread":0.1878160800095784,"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."}}