{"id":"W4323048282","doi":"10.1016/j.scitotenv.2023.162569","title":"Membrane processes for environmental remediation of nanomaterials: Potentials and challenges","year":2023,"lang":"en","type":"review","venue":"The Science of The Total Environment","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":41,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Microfiltration; Nanomaterials; Nanofiltration; Environmental remediation; Groundwater remediation; Nanotechnology; Membrane; Ultrafiltration (renal); Materials science; Chemistry; Chromatography; Contamination","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":[0.001047154,0.001148349,0.001900329,0.002330431,0.0003410856,0.001587404,0.001026328,0.001759717,0.003224954],"category_scores_gemma":[0.000739464,0.000338609,0.0007277636,0.003155489,0.0005249495,0.002181781,0.0009393651,0.001949925,0.001825762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008277683,"about_ca_system_score_gemma":0.001650642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001643781,"about_ca_topic_score_gemma":0.003643606,"domain_scores_codex":[0.9997041,0.00004594453,0.00002744279,0.00005176478,0.0001331714,0.00003769949],"domain_scores_gemma":[0.9995716,0.0001988139,0.00005903566,0.00001456202,0.0001282283,0.00002778416],"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":[0.00008558408,0.0001170573,0.0001365518,0.02827971,0.0001379866,0.0002068256,0.00006649118,0.0007653588,0.009275408,0.008309543,0.01850201,0.9341176],"study_design_scores_gemma":[0.00001393078,0.0001145985,0.0004695469,0.004169535,0.0001551955,0.0006014467,0.00007938323,0.0002176349,0.002520317,0.003067912,0.9885606,0.00002990729],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001133525,0.998664,0.0001956201,0.0002443631,0.0001186323,0.000003052739,0.00001476312,0.000004566283,0.0006416081],"genre_scores_gemma":[0.0005702126,0.9985789,0.0002450944,0.0001096392,0.00007491072,0.000003953578,0.00001727338,0.000001037111,0.0003989544],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003224954,"threshold_uncertainty_score":0.01078862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06427032937748649,"score_gpt":0.2806881726964538,"score_spread":0.2164178433189673,"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."}}