{"id":"W4387765979","doi":"10.1016/j.memsci.2023.122142","title":"Unleashing the potential of scalable, high-water vapor permeance graphene oxide membranes using electrospun supports","year":2023,"lang":"en","type":"article","venue":"Journal of Membrane Science","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Permeance; Materials science; Membrane; Oxide; Graphene; Nanotechnology; Chemical engineering; Electrospinning; Composite material; Metallurgy; Chemistry; Polymer; Engineering; Permeation","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":[0.003870083,0.0002241963,0.000392955,0.0004166914,0.0005712135,0.000127382,0.001707227,0.0000874244,0.0005386227],"category_scores_gemma":[0.000355794,0.0001324257,0.0001725059,0.002473018,0.001890338,0.001437117,0.0004229037,0.0003781251,0.00007858183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001409193,"about_ca_system_score_gemma":0.0001371518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001597257,"about_ca_topic_score_gemma":0.00001840543,"domain_scores_codex":[0.9959777,0.0001014901,0.0008602848,0.000385475,0.00192531,0.0007497552],"domain_scores_gemma":[0.9984366,0.00009628696,0.0006594805,0.0005243999,0.0001355473,0.0001476346],"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":[0.00003545607,0.00003105786,0.001077827,0.00002290289,0.00001157498,0.00005387118,0.0001845249,0.06645277,0.9313936,0.0001134972,0.000143766,0.0004791775],"study_design_scores_gemma":[0.0003425496,0.0001101411,0.0143371,0.00004292644,0.00004130568,0.0004199489,0.0003582245,0.006768441,0.9754964,0.001615593,0.0002823213,0.0001851094],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966804,0.0000588171,0.0007659354,0.001391684,0.0005369846,0.0001816609,0.00000288,0.0000654505,0.0003162212],"genre_scores_gemma":[0.9965084,0.0002132005,0.002847569,0.0001121079,0.00005938555,0.000002352079,0.000001005295,0.0000182914,0.000237748],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05968433,"threshold_uncertainty_score":0.6965028,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.011673345841347,"score_gpt":0.2448407538400719,"score_spread":0.2331674079987249,"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."}}