{"id":"W2051353463","doi":"10.1016/j.desal.2009.09.033","title":"Application of MBR for hospital wastewater treatment in China","year":2009,"lang":"en","type":"article","venue":"Desalination","topic":"Water Treatment and Disinfection","field":"Environmental Science","cited_by":104,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Fok Ying Tung Education Foundation; National Natural Science Foundation of China","keywords":"Wastewater; Effluent; Membrane bioreactor; Disinfectant; Sewage treatment; Pulp and paper industry; Waste management; Environmental science; Chlorine; Bioreactor; Chemistry; Environmental engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009876437,0.0004612184,0.0006725707,0.001119581,0.0008070659,0.0007333045,0.0005844674,0.0005466786,0.001482473],"category_scores_gemma":[0.0005368111,0.0002526738,0.0007271213,0.0007284074,0.0003022054,0.0003933179,0.0008410316,0.0002366497,0.0002301169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001542807,"about_ca_system_score_gemma":0.002268399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02492289,"about_ca_topic_score_gemma":0.02295456,"domain_scores_codex":[0.9993995,0.00012885,0.00005217881,0.0001035803,0.0001927898,0.0001230991],"domain_scores_gemma":[0.9997614,0.00003804395,0.00004319879,0.00002116513,0.00009319261,0.00004310438],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000874774,0.0004747078,0.02387982,0.001109097,0.0001567607,0.0007901576,0.0005840832,0.003398567,0.8104907,0.000608168,0.0008961253,0.1567371],"study_design_scores_gemma":[0.0004235003,0.005797836,0.1667838,0.0001620906,0.001022805,0.001786574,0.001828926,0.0159272,0.7678799,0.0006030478,0.03762648,0.0001577456],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9909419,0.003679086,0.002011613,0.0005818311,0.00005471848,0.00009301396,0.00009761779,0.00005948977,0.002480719],"genre_scores_gemma":[0.9931442,0.002439858,0.002406296,0.0001118739,0.0000354218,0.0000228876,0.00008250682,0.00001061575,0.001746387],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02492289,"threshold_uncertainty_score":0.0495556,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004768755296989534,"score_gpt":0.2252153736884398,"score_spread":0.2204466183914503,"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."}}