{"id":"W3134318717","doi":"10.1021/acs.nanolett.0c04512","title":"Highly Conductive and Permeable Nanocomposite Ultrafiltration Membranes Using Laser-Reduced Graphene Oxide","year":2021,"lang":"en","type":"article","venue":"Nano Letters","topic":"Graphene research and applications","field":"Materials Science","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; U.S. Department of Energy","keywords":"Membrane; Graphene; Materials science; Ultrafiltration (renal); Oxide; Chemical engineering; Nanocomposite; Filtration (mathematics); Water treatment; Methyl orange; Fouling; Nanotechnology; Chemistry; Photocatalysis; Chromatography; Organic chemistry; Environmental 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001595349,0.000130759,0.0001580341,0.00006980215,0.0003862804,0.0002156684,0.0001215189,0.00004583309,0.00009839514],"category_scores_gemma":[0.00002979534,0.0001261437,0.0000528139,0.0003304989,0.0001724183,0.0003250757,0.00003855475,0.00006690246,0.00002434942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003178396,"about_ca_system_score_gemma":0.00007339645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003545238,"about_ca_topic_score_gemma":0.00003077346,"domain_scores_codex":[0.9987512,0.0001105762,0.0001748878,0.000386577,0.0002495028,0.0003272063],"domain_scores_gemma":[0.9993912,0.00007400323,0.00005952065,0.0002380164,0.0001123565,0.0001249081],"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":[0.00001252865,0.00003434115,0.0001453107,0.0000291378,0.00001144335,0.00001119547,0.00009516258,0.000249875,0.9986262,0.0003377126,0.0004100978,0.00003694086],"study_design_scores_gemma":[0.0003072785,0.0000126299,0.0009581537,0.00001995094,0.00002032202,0.00004867826,0.0001184643,0.0001002693,0.9975577,0.000214329,0.0004938272,0.0001484196],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965089,0.000161008,0.0004597092,0.002360098,0.00009174463,0.0001912266,0.00003328397,0.00005897245,0.0001350643],"genre_scores_gemma":[0.9937121,0.00004158728,0.005306765,0.0007309971,0.00004577902,0.00003666478,0.00003025387,0.00001460249,0.00008123612],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004847055,"threshold_uncertainty_score":0.514399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02334975137738662,"score_gpt":0.2672171437488774,"score_spread":0.2438673923714908,"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."}}