{"id":"W1999597928","doi":"10.1139/s07-001","title":"The roles of nitrogen dissimilation and assimilation in biological nitrogen removal treating low, mid, and high strength wastewater","year":2007,"lang":"en","type":"article","venue":"Journal of Environmental Engineering and Science","topic":"Wastewater Treatment and Nitrogen Removal","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Dissimilation; Alkalinity; Denitrification; Nitrification; Effluent; Nitrogen; Chemistry; Assimilation (phonology); Chemical oxygen demand; Environmental chemistry; Wastewater; Heterotroph; Nitrogen assimilation; Biomass (ecology); Environmental engineering; Ecology; Environmental science; Biology; Bacteria","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007848871,0.0001146764,0.0001379486,0.00007968499,0.0001337932,0.00003434145,0.0000978035,0.00003948515,0.00001018096],"category_scores_gemma":[0.00002840834,0.00007100206,0.00002491596,0.0001125765,0.0004055715,0.0002729459,0.0001048164,0.00009414451,4.464105e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008380762,"about_ca_system_score_gemma":0.000004140657,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009673026,"about_ca_topic_score_gemma":0.00000782082,"domain_scores_codex":[0.9990318,0.00001783942,0.0003118829,0.0001557473,0.0002673955,0.0002152774],"domain_scores_gemma":[0.9995992,0.00009494262,0.0001313951,0.00006591967,0.000002576377,0.0001060199],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00006440865,0.00004464209,0.3200143,0.000003870375,0.000009604885,0.00002233968,0.0005262973,0.001294039,0.6644191,0.00001585895,7.268778e-7,0.01358489],"study_design_scores_gemma":[0.0008164278,0.0002882336,0.7411906,0.00004658267,0.00002281503,0.0003241339,0.0007331014,0.007425609,0.2485804,0.0003531718,0.00005751822,0.0001615183],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994097,0.0003749746,0.00005111253,0.00003398899,0.00003372493,0.00006320251,0.000002772805,0.000003055361,0.00002743984],"genre_scores_gemma":[0.9953873,0.000213794,0.004360677,0.000003481678,0.00002069529,5.188637e-7,8.309809e-7,0.000005022709,0.000007742054],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4211763,"threshold_uncertainty_score":0.289538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005766035854354326,"score_gpt":0.1923806808255677,"score_spread":0.1866146449712134,"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."}}