{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002845063,0.0004307653,0.0003336828,0.0003881205,0.0002465112,0.0003479492,0.0003382999,0.0009877048,0.0006778445],"category_scores_gemma":[0.0002324145,0.0002734561,0.0005635889,0.0002003419,0.0002254856,0.001105846,0.0002313952,0.0006443479,0.0004487979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003165851,"about_ca_system_score_gemma":0.0001966524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003848367,"about_ca_topic_score_gemma":0.0006591697,"domain_scores_codex":[0.999862,0.00001210117,0.0000118041,0.00003463764,0.00005614999,0.00002333699],"domain_scores_gemma":[0.9998598,0.00002788087,0.00004028149,0.000009637502,0.00003972838,0.00002265032],"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":[0.000008918831,0.00001674866,0.00002655122,0.00006386167,0.000003985444,0.00005779868,0.00001296388,0.00007189746,0.9976324,0.0001310932,0.00003716275,0.001936515],"study_design_scores_gemma":[0.000006427372,0.00009941745,0.0006178899,0.00000692592,0.000007118707,0.0002042444,0.000009766973,0.0007576871,0.9951347,0.00004552748,0.00310058,0.000009708754],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.90475,0.01236558,0.07520076,0.0006996911,0.0003769721,0.0002853975,0.0004524686,0.0007867889,0.005082331],"genre_scores_gemma":[0.8852289,0.009653013,0.09267329,0.0003260591,0.0001388354,0.0002923592,0.0004628873,0.0001124251,0.0111122],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009877048,"threshold_uncertainty_score":0.002297044,"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."}}