{"id":"W2803607456","doi":"10.2166/wst.2001.0145","title":"Modelling biological phosphorus removal from a cheese factory effluent by an SBR","year":2001,"lang":"en","type":"article","venue":"Water Science & Technology","topic":"Wastewater Treatment and Nitrogen Removal","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydromantis Environmental Software Solutions (Canada); Polytechnique Montréal","funders":"","keywords":"Effluent; Sequencing batch reactor; Phosphorus; Factory (object-oriented programming); Activated sludge model; Enhanced biological phosphorus removal; Calibration; Environmental science; Process engineering; Pulp and paper industry; Environmental engineering; Waste management; Biochemical engineering; Chemistry; Engineering; Mathematics; Activated sludge; Computer science; Sewage treatment; Statistics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003017983,0.0002741282,0.0002388509,0.0001873193,0.000412946,0.00007673549,0.001214428,0.0002435881,0.0007834312],"category_scores_gemma":[0.000008481619,0.0001729156,0.00005977103,0.000741861,0.001957886,0.0005142668,0.0006449766,0.0002214516,0.001122221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002840892,"about_ca_system_score_gemma":0.00001471035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001028334,"about_ca_topic_score_gemma":0.0000168175,"domain_scores_codex":[0.9973102,0.00003279886,0.0002537289,0.001006577,0.0004227894,0.0009739413],"domain_scores_gemma":[0.9990814,0.000006987107,0.00004925366,0.0006380285,0.00001383217,0.0002104638],"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":[0.0000370101,0.0001919784,0.03492534,2.733123e-7,0.000006148538,0.0001357801,0.000408885,0.001346673,0.9572406,0.00002651436,0.00005315531,0.005627625],"study_design_scores_gemma":[0.0004923514,0.000345641,0.001111467,0.000004775158,0.00001322231,0.0001446649,0.0002347453,0.01421404,0.9610933,0.004811039,0.01712933,0.0004054352],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962924,0.0001439116,0.001764247,0.0004201143,0.0001508318,0.0001992323,0.000009091801,0.0003436996,0.0006764984],"genre_scores_gemma":[0.9889302,0.00006486355,0.0104408,0.0001155035,0.00002374217,0.00002214962,0.00002366709,0.00001463445,0.0003644313],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03381388,"threshold_uncertainty_score":0.9996555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01942550291248121,"score_gpt":0.223740503792873,"score_spread":0.2043150008803918,"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."}}