{"id":"W3082615682","doi":"10.1016/j.memsci.2020.118681","title":"Polyamide reverse osmosis membranes containing 1D nanochannels for enhanced water purification","year":2020,"lang":"en","type":"article","venue":"Journal of Membrane Science","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":63,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"The Ministry of Economic Affairs and Employment; National Natural Science Foundation of China; Thalassemia Foundation of Canada","keywords":"Membrane; Reverse osmosis; Polyamide; Thin-film composite membrane; Chemical engineering; Desalination; Materials science; Forward osmosis; Interfacial polymerization; Permeability (electromagnetism); Osmotic power; Layer (electronics); Chromatography; Nanotechnology; Chemistry; Polymer chemistry; Polymer; Composite material; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002112997,0.0002771401,0.0002353148,0.0001612448,0.0001971839,0.0003097544,0.0002376509,0.0003939279,0.0006340088],"category_scores_gemma":[0.0002637988,0.0001676665,0.0002473656,0.000117365,0.0001672505,0.0006084472,0.0002957924,0.0004425392,0.0002883336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005726844,"about_ca_system_score_gemma":0.0004002484,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008786417,"about_ca_topic_score_gemma":0.001842923,"domain_scores_codex":[0.9998577,0.00001404396,0.00001054994,0.00003636589,0.00004546512,0.00003592176],"domain_scores_gemma":[0.9998844,0.00002858363,0.00003403697,0.00001202147,0.00002939884,0.00001152636],"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":[0.00002338134,0.000007585963,0.00004176747,0.00004227605,0.000003150224,0.0000143499,0.00001140052,0.0001379316,0.997326,0.000205563,0.00008936587,0.002097254],"study_design_scores_gemma":[0.000003897752,0.00003223313,0.0002316136,0.000003558115,0.00000620377,0.00002928301,0.000006136045,0.001364278,0.9966946,0.00002936988,0.001593028,0.000005817224],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9718857,0.0029388,0.02140272,0.0002359297,0.0001672146,0.00004383339,0.0002110955,0.0004468465,0.002667893],"genre_scores_gemma":[0.9794441,0.001490252,0.01625561,0.0001030761,0.00002389487,0.00004665268,0.0001270355,0.00004115125,0.002468196],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008786417,"threshold_uncertainty_score":0.004155099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02692729193642586,"score_gpt":0.2627705344988761,"score_spread":0.2358432425624502,"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."}}