{"id":"W2940598562","doi":"10.1002/pat.4626","title":"Cellulose acetate nanocomposite ultrafiltration membranes tailored with hydrous manganese dioxide nanoparticles for water treatment applications","year":2019,"lang":"en","type":"article","venue":"Polymers for Advanced Technologies","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Membrane; Ultrafiltration (renal); Nanocomposite; Cellulose acetate; Materials science; Chemical engineering; Permeation; Contact angle; Nanoparticle; Cellulose; Fouling; Manganese; Regenerated cellulose; Nuclear chemistry; Chromatography; Chemistry; Nanotechnology; Composite material; Metallurgy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007736265,0.0003477821,0.0003322326,0.00012216,0.0002395703,0.00004461001,0.0004435396,0.0001650109,0.00006874017],"category_scores_gemma":[0.00002073654,0.0002322974,0.0001125911,0.0002696768,0.000412336,0.0005968752,0.00008357195,0.00007489728,0.0001649914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001856629,"about_ca_system_score_gemma":0.00001009807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003443163,"about_ca_topic_score_gemma":0.00006662164,"domain_scores_codex":[0.9982117,0.00001315609,0.0003162525,0.0006719478,0.0001911218,0.0005957765],"domain_scores_gemma":[0.9989796,0.0001223248,0.0001497096,0.0006847325,0.00002173769,0.00004187022],"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":[0.000276851,0.00009975878,0.0003262134,0.00005778376,0.00004032066,9.535724e-7,0.0001444367,0.004357299,0.9598304,0.000694657,0.00001502492,0.03415631],"study_design_scores_gemma":[0.001603413,0.0008435753,0.00002922621,0.0000105205,0.00005954493,0.00001077365,0.0009385617,0.0004881218,0.9776876,0.002320141,0.01564217,0.0003663631],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9826123,0.0003346333,0.008283821,0.00166752,0.00005806941,0.004692576,0.00003939853,0.001976212,0.0003354741],"genre_scores_gemma":[0.9737537,0.0001195215,0.01814832,0.00004051243,0.000007228265,0.005634614,0.0001097339,0.00004778453,0.002138598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03378995,"threshold_uncertainty_score":0.9472815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007457123705336665,"score_gpt":0.2252008024201846,"score_spread":0.217743678714848,"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."}}