{"id":"W1988463914","doi":"10.1016/j.watres.2010.08.030","title":"Biological nitrogen removal with a real-time control strategy using moving slope changes of pH(mV)- and ORP-time profiles","year":2010,"lang":"en","type":"article","venue":"Water Research","topic":"Wastewater Treatment and Nitrogen Removal","field":"Environmental Science","cited_by":57,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"National Key Research and Development Program of China","keywords":"Anoxic waters; Hydraulic retention time; Chemistry; Nitrogen; Volume (thermodynamics); Reduction potential; Sequencing batch reactor; Anaerobic exercise; Oxygen; Pulp and paper industry; Environmental chemistry; Analytical Chemistry (journal); Environmental engineering; Wastewater; Environmental science; Inorganic chemistry","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":[0.0002791548,0.0004963618,0.000440174,0.0002181181,0.0001501495,0.0006158712,0.0004327095,0.00046355,0.0003617861],"category_scores_gemma":[0.0003775038,0.0001733968,0.0002500244,0.0002741905,0.0002250197,0.0003553988,0.0002267826,0.0003096153,0.00009955348],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004466156,"about_ca_system_score_gemma":0.0004032181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002689803,"about_ca_topic_score_gemma":0.003599978,"domain_scores_codex":[0.9997587,0.00002145123,0.00001477152,0.00009388754,0.00008821188,0.00002298692],"domain_scores_gemma":[0.9998482,0.00002556514,0.00004022717,0.00001665546,0.00004892175,0.00002031934],"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":[0.0002780019,0.00007032925,0.0003440036,0.00003149743,0.000006565289,0.00001342031,0.00001368608,0.0006829869,0.989974,0.00002714425,0.00003325038,0.008525006],"study_design_scores_gemma":[0.00002549168,0.0005472485,0.002896906,0.000002494035,0.0000207049,0.00004959126,0.00001632518,0.02520417,0.9707232,0.00003055786,0.0004628676,0.00002050484],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9673794,0.0002709152,0.0307639,0.0001025944,0.00007192443,0.00007094324,0.0001185036,0.0003373955,0.0008844447],"genre_scores_gemma":[0.9806285,0.0001307624,0.01833036,0.00003738388,0.00001041021,0.00003948728,0.0000573538,0.00001429014,0.0007515945],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002689803,"threshold_uncertainty_score":0.005348265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04406633321909487,"score_gpt":0.2882791196121,"score_spread":0.2442127863930051,"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."}}