{"id":"W2961627480","doi":"10.5360/membrane.35.119","title":"Development of Novel Membranes Based on Electro–spun Nanofibers and Their Application in Liquid Filtration, Membrane Distillation and Membrane Adsorption","year":2010,"lang":"en","type":"article","venue":"MEMBRANE","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Membrane; Nanofiber; Materials science; Polyvinylidene fluoride; Polysulfone; Nanofiltration; Chemical engineering; Desalination; Membrane distillation; Electrospinning; Filtration (mathematics); Polyacrylonitrile; Bacterial cellulose; Synthetic membrane; Polymer; Ultrafiltration (renal); Cellulose acetate; Polymer chemistry; Chromatography; Cellulose; Chemistry; Nanotechnology; Composite material","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007598482,0.0003704107,0.0004049369,0.0002785933,0.000163656,0.00004160474,0.0002575308,0.0002843908,0.0002419914],"category_scores_gemma":[0.0001229975,0.0003292063,0.00004432422,0.0005988849,0.0003624501,0.0003688163,0.00008697822,0.0003090127,0.00002345081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008720777,"about_ca_system_score_gemma":0.00005088265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001185554,"about_ca_topic_score_gemma":0.001131183,"domain_scores_codex":[0.9977313,0.0000588773,0.0007054123,0.0007114529,0.000429936,0.000363029],"domain_scores_gemma":[0.9988198,0.0002110802,0.0003151663,0.0005083982,0.00003381624,0.0001117321],"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":[0.0002438456,0.0001816654,0.0007392484,0.0001211868,0.000008640887,4.18657e-7,0.0006426966,0.002083489,0.9884034,0.0005621705,0.000007814603,0.007005406],"study_design_scores_gemma":[0.001256752,0.0001351892,0.00664494,0.00003656118,0.00001144794,0.00001078383,0.0001217961,0.0484896,0.9404746,0.00007570419,0.002395774,0.000346825],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908791,0.00002629311,0.005691378,0.0005643585,0.00008768788,0.0008442353,0.00001397388,0.0001547073,0.001738291],"genre_scores_gemma":[0.9859698,0.00005870742,0.01345825,0.000140044,0.00002472529,0.0001421281,0.0001027622,0.00003417124,0.00006937511],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04792878,"threshold_uncertainty_score":0.999916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009534834847850195,"score_gpt":0.2213417533356011,"score_spread":0.2118069184877509,"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."}}