{"id":"W2407272075","doi":"10.2175/106143007x221085","title":"Denitrification with Carbon Addition—Kinetic Considerations","year":2008,"lang":"en","type":"article","venue":"Water Environment Research","topic":"Wastewater Treatment and Nitrogen Removal","field":"Environmental Science","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"EnviroSim (Canada)","funders":"","keywords":"Heterotroph; Methanol; Effluent; Chemistry; Pulp and paper industry; Wastewater; Denitrification; Carbon fibers; Nitrogen; Sewage treatment; Environmental engineering; Sugar; Environmental chemistry; Environmental science; Organic chemistry; Biology; Materials science; Bacteria","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001906163,0.001567167,0.001721152,0.000580652,0.0005297172,0.001605865,0.002333369,0.001059278,0.001351491],"category_scores_gemma":[0.002468947,0.0007556374,0.0009841167,0.0005308089,0.0004049578,0.003267496,0.0007132718,0.002010441,0.0006929204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002062953,"about_ca_system_score_gemma":0.001047211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009066011,"about_ca_topic_score_gemma":0.009160983,"domain_scores_codex":[0.9989225,0.0003043052,0.0001299446,0.0001780698,0.0003029295,0.0001623158],"domain_scores_gemma":[0.9993221,0.0003746644,0.00006300385,0.00003739992,0.0001799152,0.00002295117],"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":[0.001963704,0.001419636,0.007453957,0.006304199,0.0004093218,0.001717107,0.0003878121,0.1421836,0.6908928,0.06237046,0.001984359,0.08291298],"study_design_scores_gemma":[0.0001191176,0.001136512,0.004276517,0.0001862387,0.0002459444,0.001049464,0.0002907176,0.4016571,0.5552345,0.01515472,0.02041927,0.000229922],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6898144,0.04227576,0.2112386,0.004175895,0.0005683302,0.001267093,0.002441125,0.0003844792,0.04783438],"genre_scores_gemma":[0.9206916,0.02152812,0.04248421,0.0002783173,0.00008789481,0.0004611265,0.0008889722,0.0001121709,0.01346755],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009066011,"threshold_uncertainty_score":0.01802647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05080568204570344,"score_gpt":0.2538026970265648,"score_spread":0.2029970149808614,"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."}}