{"id":"W2164522454","doi":"10.1680/jees.2013.0033","title":"Membrane concentrate management options: a comprehensive critical review","year":2013,"lang":"en","type":"article","venue":"Journal of Environmental Engineering and Science","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Bureau of Reclamation","keywords":"Nanofiltration; Reverse osmosis; Pollutant; Water quality; Natural organic matter; Membrane technology; Water treatment; Environmental science; Waste management; Membrane; Biochemical engineering; Environmental engineering; Chemistry; Engineering; Ecology; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0002571411,0.0001078552,0.0001589402,0.00006322935,0.00009512429,0.00004728883,0.000280837,0.00002287347,0.00117522],"category_scores_gemma":[0.00005824284,0.00008800485,0.00003600411,0.0001944944,0.0006584451,0.000660427,0.000173993,0.0001349312,0.000135476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001100819,"about_ca_system_score_gemma":0.000004177855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002830066,"about_ca_topic_score_gemma":4.859036e-8,"domain_scores_codex":[0.9988726,0.00001240276,0.0002899065,0.0001677235,0.0004386009,0.0002187264],"domain_scores_gemma":[0.9995747,0.00004416629,0.00008377928,0.000142906,0.000006575981,0.0001479359],"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":[0.000005815531,0.0001370788,0.0008348217,0.0003187204,0.00002422969,0.00005997856,0.000117377,0.01056917,0.966493,0.001627706,0.002055152,0.01775694],"study_design_scores_gemma":[0.003704842,0.001850169,0.6106531,0.005023328,0.0004450975,0.004931304,0.00280891,0.1034976,0.1427855,0.001984918,0.1192948,0.003020451],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9885494,0.006396749,0.00114915,0.001398484,0.0002471157,0.0003667412,0.00000271666,0.00004073554,0.001848914],"genre_scores_gemma":[0.9754888,0.01316959,0.01090026,0.0003049783,0.00001157907,0.00000840785,2.303302e-7,0.000005940743,0.0001102412],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8237075,"threshold_uncertainty_score":0.9997379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01216518839598715,"score_gpt":0.2307416849138403,"score_spread":0.2185764965178532,"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."}}