{"id":"W4378417826","doi":"10.1016/j.seppur.2023.124176","title":"Composite membranes with multifunctionalities for processing textile wastewater: Simultaneous oil/water separation and dye adsorption/degradation","year":2023,"lang":"en","type":"article","venue":"Separation and Purification Technology","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":44,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Membrane; Chemical engineering; Adsorption; Filtration (mathematics); Materials science; Wastewater; Emulsion; Polyacrylonitrile; Nanofiltration; Chromatography; Chemistry; Waste management; Composite material; Organic chemistry; Polymer","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":[0.000418104,0.0004632792,0.0003210556,0.0004520708,0.0002574803,0.0003946851,0.0002193416,0.0007196335,0.0007508941],"category_scores_gemma":[0.0003801407,0.000257649,0.0005044155,0.0002519697,0.0002043276,0.0004732438,0.0003718357,0.0005065408,0.0004000657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000299447,"about_ca_system_score_gemma":0.000170814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003502354,"about_ca_topic_score_gemma":0.0009743352,"domain_scores_codex":[0.9997919,0.00003438587,0.00001726697,0.00004390372,0.00005744842,0.00005506004],"domain_scores_gemma":[0.9998046,0.00005019791,0.00004041771,0.00001502642,0.00006239324,0.00002756149],"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":[0.00006585294,0.00001106425,0.00004207179,0.00004249471,0.000004726649,0.00001520383,0.000009904858,0.00005116712,0.9983379,0.00005554043,0.00002179496,0.001342284],"study_design_scores_gemma":[0.000004405445,0.00008838611,0.0003503699,0.000002332562,0.00001157763,0.00004773883,0.000005545679,0.0003983671,0.9983904,0.00001543075,0.0006826082,0.000002882633],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9705018,0.003636814,0.02324325,0.0001595626,0.00008671391,0.00004797015,0.0001144412,0.0001932486,0.002016193],"genre_scores_gemma":[0.9839476,0.001109523,0.01169397,0.0001034201,0.00003955087,0.00004783383,0.000114202,0.00003305203,0.002910935],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007508941,"threshold_uncertainty_score":0.002512038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01509752953500308,"score_gpt":0.2652312462684006,"score_spread":0.2501337167333975,"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."}}