{"id":"W2778392461","doi":"10.1016/j.jenvman.2017.12.018","title":"A 3DBER-S-EC process for simultaneous nitrogen and phosphorus removal from wastewater with low organic carbon content","year":2017,"lang":"en","type":"article","venue":"Journal of Environmental Management","topic":"Wastewater Treatment and Nitrogen Removal","field":"Environmental Science","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Northern British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Denitrifying bacteria; Electrocoagulation; Effluent; Chemistry; Phosphorus; Wastewater; Sulfur; Hydraulic retention time; Nitrogen; Denitrification; Environmental chemistry; Pulp and paper industry; Sewage treatment; Environmental engineering; Environmental science; Organic chemistry","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":[0.0002176928,0.000462093,0.0004904647,0.0002379042,0.000284419,0.0004218859,0.0004608099,0.0006905168,0.0007677894],"category_scores_gemma":[0.0001096917,0.0001713386,0.0005521781,0.0002775452,0.0001930786,0.0003559398,0.0003912862,0.000439074,0.0003526199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003592418,"about_ca_system_score_gemma":0.0005962455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002483881,"about_ca_topic_score_gemma":0.005169283,"domain_scores_codex":[0.999792,0.00001668686,0.00001635537,0.00004406136,0.00009259181,0.00003834383],"domain_scores_gemma":[0.9999564,0.000008137727,0.000008894503,0.000004114861,0.00001120628,0.00001126642],"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":[0.00008796018,0.00003897696,0.00009245626,0.0000570064,0.000004904878,0.0000623825,0.000009232466,0.0001607209,0.9953575,0.00006081317,0.00003724464,0.004030861],"study_design_scores_gemma":[0.00001026024,0.0001359839,0.0007439189,0.000002448754,0.00001271478,0.0001044018,0.00001012215,0.001624314,0.9966958,0.00001759319,0.0006355073,0.000007008507],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9879367,0.0009009507,0.009254396,0.00006016496,0.00005704035,0.00003049326,0.00009480319,0.0001335647,0.001532014],"genre_scores_gemma":[0.9831798,0.0007098667,0.01207969,0.00008259722,0.00001461924,0.00002310688,0.0001897635,0.00002650918,0.00369406],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002483881,"threshold_uncertainty_score":0.0049389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00996000430880879,"score_gpt":0.2022346945117008,"score_spread":0.192274690202892,"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."}}