{"id":"W2284906057","doi":"10.1016/j.biortech.2016.02.065","title":"Nitrification cessation and recovery in an aerated saturated vertical subsurface flow treatment wetland: Field studies and microscale biofilm modeling","year":2016,"lang":"en","type":"article","venue":"Bioresource Technology","topic":"Constructed Wetlands for Wastewater Treatment","field":"Environmental Science","cited_by":46,"is_retracted":false,"has_abstract":false,"ca_institutions":"Royal Military College of Canada; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Helmholtz-Zentrum für Umweltforschung; Bundesministerium für Bildung und Forschung; Harper Adams University","keywords":"Nitrification; Aeration; Effluent; Environmental engineering; Environmental science; Nitrate; Subsurface flow; Biofilm; Sewage treatment; Wastewater; Environmental chemistry; Chemistry; Ecology; Nitrogen; Biology; Groundwater; Bacteria; Geology","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":[0.0001953272,0.0002300928,0.0003174271,0.0001079676,0.0003483835,0.0003132393,0.000375653,0.0003946034,0.0002683641],"category_scores_gemma":[0.0002477603,0.0001741829,0.0003161031,0.00009646949,0.0002410208,0.0003361572,0.0001650673,0.0003806197,0.00004489724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007700906,"about_ca_system_score_gemma":0.0005473489,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02351353,"about_ca_topic_score_gemma":0.01830056,"domain_scores_codex":[0.9999355,0.000006448594,0.000004839604,0.0000190758,0.00001497114,0.00001907162],"domain_scores_gemma":[0.999898,0.00004348408,0.00001688915,0.000006221377,0.00001959312,0.00001583722],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001592443,0.001257782,0.0106263,0.0001169173,0.00003738009,0.0001989075,0.0001919193,0.03982428,0.9358578,0.0003449751,0.0002758398,0.00967555],"study_design_scores_gemma":[0.0001912328,0.002833067,0.04447085,0.000008394502,0.00006288268,0.00007535925,0.0003545353,0.5464036,0.4048115,0.0003306007,0.0004058198,0.00005210936],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999686,0.000009526445,0.0001861173,0.000009400906,0.00000151329,0.000002945144,0.00002441111,0.000003370955,0.00007667459],"genre_scores_gemma":[0.9993318,0.00002168262,0.0003471173,0.000003244365,9.49144e-7,0.000007996196,0.00002938817,0.00000169113,0.0002561619],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02351353,"threshold_uncertainty_score":0.04675335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01670571718621027,"score_gpt":0.2449783582637784,"score_spread":0.2282726410775681,"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."}}