{"id":"W2398877736","doi":"10.1002/cjce.22542","title":"MBBR followed by microfiltration and reverse osmosis as a compact alternative for advanced treatment of a pesticide‐producing industry wastewater towards reuse","year":2016,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Reverse osmosis; Effluent; Moving bed biofilm reactor; Chemical oxygen demand; Microfiltration; Environmental science; Wastewater; Nanofiltration; Powdered activated carbon treatment; Industrial wastewater treatment; Reuse; Sewage treatment; Pulp and paper industry; Total suspended solids; Chemistry; Waste management; Environmental engineering; Activated carbon; Adsorption; Membrane; Engineering; Biofilm","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002120489,0.0005050568,0.0005777882,0.0002797505,0.0001535075,0.0004571307,0.0004539847,0.0006620333,0.0005205396],"category_scores_gemma":[0.000196236,0.0002432206,0.0005138012,0.000181587,0.0001943371,0.0003372983,0.0003489313,0.000490365,0.0003918417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002221815,"about_ca_system_score_gemma":0.0002005527,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007926897,"about_ca_topic_score_gemma":0.001015954,"domain_scores_codex":[0.99979,0.00002674432,0.00001376055,0.00003976851,0.0000987733,0.0000310381],"domain_scores_gemma":[0.9999115,0.00001353313,0.00003339247,0.00001021836,0.00001596694,0.0000153532],"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":[0.00004074025,0.00003243706,0.00004678485,0.00003252203,0.000003927871,0.00001988572,0.000006082063,0.00009242037,0.9977419,0.00002265474,0.00001885963,0.00194172],"study_design_scores_gemma":[0.00002809527,0.0006735453,0.002294608,0.000009402357,0.00002572842,0.0001903878,0.00001685233,0.003060986,0.9919744,0.00001947187,0.001693049,0.00001328494],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9847387,0.001769919,0.01234649,0.00009933293,0.0000577819,0.00005885848,0.00007756727,0.0002440698,0.0006072607],"genre_scores_gemma":[0.9850999,0.0006803978,0.01274464,0.00004556994,0.00002211359,0.00003883292,0.0001005616,0.00002092204,0.001247102],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007926897,"threshold_uncertainty_score":0.00174135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01244554262792909,"score_gpt":0.2259989989550893,"score_spread":0.2135534563271602,"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."}}