{"id":"W2528441821","doi":"10.2965/jwet.16-026","title":"Dynamic Simulation of Trickling Filter Process with Hydraulic Stress Tests","year":2016,"lang":"en","type":"article","venue":"Journal of Water and Environment Technology","topic":"Wastewater Treatment and Nitrogen Removal","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydromantis Environmental Software Solutions (Canada)","funders":"Japan Society for the Promotion of Science","keywords":"Trickling filter; Effluent; Nitrification; Wastewater; Filter (signal processing); Activated sludge; Environmental science; Sewage treatment; Hydraulic retention time; Environmental engineering; Pulp and paper industry; Chemistry; Nitrogen; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008423877,0.0001181416,0.0001856028,0.0001147474,0.00003597354,0.00000533404,0.0001251053,0.00007662942,0.00019039],"category_scores_gemma":[0.000003674683,0.00005291117,0.00003233422,0.00005556732,0.0002306166,0.0002047504,0.00007127661,0.00006630514,0.00001788241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006256909,"about_ca_system_score_gemma":0.000002387419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002352494,"about_ca_topic_score_gemma":0.000002090563,"domain_scores_codex":[0.9992157,0.00001408152,0.0002573907,0.0001386568,0.0001927192,0.0001814942],"domain_scores_gemma":[0.9996628,0.00001914618,0.0001518152,0.000116806,0.000005577972,0.00004382986],"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":[0.0002871984,0.000338222,0.3570348,0.00002518873,0.0001205914,0.00009270702,0.0004900889,0.02164983,0.5731093,0.000002784521,0.000008423956,0.04684088],"study_design_scores_gemma":[0.003228524,0.001905177,0.03771966,0.0001335707,0.0001606615,0.00033808,0.0001987384,0.001451476,0.9510762,0.002685218,0.000810965,0.0002917193],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975168,0.00005502615,0.001662392,0.0006110082,0.00001703311,0.0000816292,0.000002198832,0.000009293941,0.00004465444],"genre_scores_gemma":[0.9978474,0.00007569598,0.001911997,0.000009053455,0.000008011591,0.000002327742,0.000001008512,0.00001023539,0.0001342132],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3779669,"threshold_uncertainty_score":0.2157655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005326329611357853,"score_gpt":0.2047085227166357,"score_spread":0.1993821931052778,"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."}}