{"id":"W2030925581","doi":"10.1002/cjce.21623","title":"Studies of extraction of methylene blue from synthetic waste water using liquid emulsion membrane technology","year":2012,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Diluent; Extraction (chemistry); Emulsion; Kerosene; Methylene blue; Membrane; Permeation; Chromatography; Wastewater; Pulmonary surfactant; Phase (matter); Chemistry; Materials science; Waste management; Nuclear chemistry; Organic chemistry; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000343788,0.0002557581,0.0003802336,0.0002108199,0.0002366844,0.0002637772,0.0002182943,0.000325206,0.0004364864],"category_scores_gemma":[0.0004086942,0.0001393023,0.0003598316,0.0003116213,0.0002040478,0.0004736184,0.000268448,0.0003423385,0.0002760073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002633598,"about_ca_system_score_gemma":0.0002529171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001024648,"about_ca_topic_score_gemma":0.00112218,"domain_scores_codex":[0.9997558,0.00006226051,0.00001836919,0.00003376037,0.0000929809,0.00003689735],"domain_scores_gemma":[0.9998695,0.00005139871,0.00002204067,0.000007235559,0.00003851242,0.0000112787],"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":[0.00005330486,0.00002555442,0.0001515345,0.0001390678,0.000007059003,0.00007570572,0.00004296904,0.0001533713,0.9973478,0.00003502983,0.000008266595,0.001960378],"study_design_scores_gemma":[0.000004442201,0.0002325837,0.0008005084,0.000007334954,0.00001079746,0.0001270998,0.00003203972,0.0004532623,0.9975477,0.00002044674,0.0007597077,0.000004094089],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9886594,0.002328214,0.00773717,0.00007100843,0.000008752082,0.0000426282,0.00008672507,0.00002785032,0.001038296],"genre_scores_gemma":[0.9887832,0.003210937,0.005832749,0.00004693587,0.000006412115,0.00002726247,0.0001926772,0.00001727596,0.001882679],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001024648,"threshold_uncertainty_score":0.002037406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02221958806660982,"score_gpt":0.2549319529624283,"score_spread":0.2327123648958185,"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."}}