{"id":"W4379466705","doi":"10.29169/1927-5129.2023.19.08","title":"A Mini Review on Treatment of Wastewater with Membrane Technology","year":2023,"lang":"en","type":"review","venue":"Journal of Basic & Applied Sciences","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Filtration (mathematics); Reverse osmosis; Flocculation; Membrane; Membrane technology; Microfiltration; Coagulation; Wastewater; Water treatment; Process engineering; Sewage treatment; Biochemical engineering; Waste management; Environmental science; Engineering; Chemistry; Environmental engineering; Mathematics; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009173692,0.0004158994,0.002113268,0.0005854768,0.0001122684,0.0000246225,0.00116858,0.000207606,0.0004094939],"category_scores_gemma":[0.00006597064,0.0002017731,0.0002954873,0.0023715,0.0012953,0.0001048809,0.0001225277,0.0002572715,0.0003870078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002449186,"about_ca_system_score_gemma":0.0001905556,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004826029,"about_ca_topic_score_gemma":0.00000985789,"domain_scores_codex":[0.9970127,0.00006307651,0.001181718,0.0004466789,0.0009592345,0.0003365287],"domain_scores_gemma":[0.9972699,0.0002218562,0.001935573,0.0004785161,0.00002083318,0.0000732646],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001776939,0.0001951783,0.000006789562,0.00560081,0.0001318486,0.00005562034,0.00005951663,0.00007256222,0.0002141538,0.0003624373,0.001311433,0.9919719],"study_design_scores_gemma":[0.000338126,0.002799511,0.000002419068,0.02314264,0.0006785903,0.0003103243,0.0001679699,0.00000185296,0.004358623,0.0003306391,0.9675043,0.0003650062],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0008929735,0.9919803,0.000005853718,0.0005729682,0.0001264635,0.001046575,0.000007847705,0.00006455559,0.005302425],"genre_scores_gemma":[0.0001729503,0.9978743,0.001361958,0.00003973688,0.00003294503,0.00007709541,0.000001554557,0.00002295441,0.0004164572],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9916069,"threshold_uncertainty_score":0.8228068,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0631827394417377,"score_gpt":0.3251029563487612,"score_spread":0.2619202169070235,"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."}}