{"id":"W3023631711","doi":"10.1016/j.bej.2020.107630","title":"Single reactor nitritation-denitritation for high strength digested biosolid thickening lagoon supernatant treatment","year":2020,"lang":"en","type":"article","venue":"Biochemical Engineering Journal","topic":"Wastewater Treatment and Nitrogen Removal","field":"Environmental Science","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates","keywords":"Denitrifying bacteria; Chemistry; Hydraulic retention time; Nitrosomonas; Pulp and paper industry; Alkalinity; Sequencing batch reactor; Nitrification; Denitrification; Wastewater; Environmental chemistry; Nitrogen; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006431865,0.0002192594,0.00019299,0.00003984191,0.0000982842,0.00009038901,0.0001444889,0.00009244786,0.0001277332],"category_scores_gemma":[0.000138389,0.0001805241,0.0001242659,0.0001790583,0.00002705014,0.0001921762,0.00003504639,0.0001347607,0.0000454966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003219115,"about_ca_system_score_gemma":0.00001411063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002037109,"about_ca_topic_score_gemma":7.924809e-7,"domain_scores_codex":[0.9988878,0.00001528684,0.0002861732,0.0002470143,0.0002490382,0.0003146324],"domain_scores_gemma":[0.999422,0.000103529,0.00008007197,0.00008825397,0.00002128043,0.0002848712],"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":[0.00009622076,0.0001230993,0.0005360875,0.000009673277,0.00006014206,0.00002200875,0.0003317075,0.0005255875,0.9966986,0.00002588453,0.0004654138,0.001105581],"study_design_scores_gemma":[0.001954976,0.0006695384,0.0006755643,0.0000261598,0.0000826623,0.0000570766,0.00009133439,0.004851184,0.9880781,0.00005331114,0.003176701,0.0002833619],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961116,0.0001344504,0.002367159,0.0009132769,0.0001292079,0.0002015266,0.00003459235,0.00008437649,0.00002378859],"genre_scores_gemma":[0.9559708,0.0000211945,0.04341649,0.00004299661,0.000375785,0.00001564297,0.0000920638,0.00003306292,0.00003196306],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04104934,"threshold_uncertainty_score":0.736156,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01894668105134935,"score_gpt":0.2078183753168841,"score_spread":0.1888716942655348,"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."}}