{"id":"W2025799600","doi":"10.1061/(asce)0733-9372(2006)132:7(810)","title":"Operational Optimization and Mass Balances in a Two-Stage MBR Treating High Strength Pet Food Wastewater","year":2006,"lang":"en","type":"article","venue":"Journal of Environmental Engineering","topic":"Wastewater Treatment and Nitrogen Removal","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Kjeldahl method; Total suspended solids; Chemical oxygen demand; Biochemical oxygen demand; Chemistry; Effluent; Volatile suspended solids; Wastewater; Suspended solids; Nitrification; Pulp and paper industry; Hydraulic retention time; Mixed liquor suspended solids; Total dissolved solids; Membrane bioreactor; Dissolved air flotation; Nitrogen; Environmental engineering; Environmental chemistry; Environmental science; Activated sludge","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":[0.0001060506,0.0001525881,0.0001625096,0.00007107292,0.00004154713,0.00003914246,0.00007569126,0.00002110205,0.0004225769],"category_scores_gemma":[0.000002868678,0.0001277688,0.00004242934,0.00005808714,0.00003351692,0.0004165821,0.00004507909,0.0001028275,0.000005993979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002003934,"about_ca_system_score_gemma":0.000002810288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005930692,"about_ca_topic_score_gemma":0.00001253253,"domain_scores_codex":[0.9991003,0.00001862424,0.0003186539,0.0001388619,0.0002379691,0.0001855654],"domain_scores_gemma":[0.9997615,0.0000219744,0.00009961852,0.00005874385,0.000001064441,0.00005709704],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001447883,0.0000719864,0.06031453,0.000003852911,0.00001490886,0.00006648287,0.00004237052,0.7640152,0.1753304,0.00001251615,0.000003852707,0.0001094337],"study_design_scores_gemma":[0.007650277,0.0008287771,0.307025,0.0001312838,0.00009859476,0.0007754984,0.0004054887,0.5190793,0.1625419,0.00009355001,0.000524974,0.000845461],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990888,0.0001214171,0.0004922788,0.00002964515,0.00005847002,0.00008794117,0.00001441698,0.000006772362,0.000100314],"genre_scores_gemma":[0.9495585,0.00002193949,0.05015743,0.000006621127,0.00007758335,0.000004395044,0.00001466155,0.00001584568,0.000143038],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2467104,"threshold_uncertainty_score":0.5210261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003107071690364732,"score_gpt":0.1697677872808424,"score_spread":0.1666607155904777,"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."}}