{"id":"W2768051550","doi":"10.1016/j.carbpol.2017.10.095","title":"Synergistic effect of carbon nanotubes and graphene for high performance cellulose acetate membranes in biomedical applications","year":2017,"lang":"en","type":"article","venue":"Carbohydrate Polymers","topic":"Graphene and Nanomaterials Applications","field":"Engineering","cited_by":75,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"European Regional Development Fund; Ontario Ministry of Research, Innovation and Science","keywords":"Cellulose acetate; Membrane; Biocompatibility; Graphene; Cellulose; Chemical engineering; Carbon nanotube; Chemistry; Permeation; Bovine serum albumin; Ethanol; Nanomaterials; Solvent; Materials science; Organic chemistry; Nanotechnology; Chromatography; Biochemistry","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":[0.0001469124,0.0001764215,0.0003124229,0.0001855293,0.0001083812,0.00003098499,0.000217575,0.00009402763,0.000004272372],"category_scores_gemma":[0.00001435233,0.0001625054,0.00004194049,0.0001485333,0.0002388198,0.00007276977,0.00003215153,0.00005080021,0.000001055203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001380149,"about_ca_system_score_gemma":0.00001273649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002376931,"about_ca_topic_score_gemma":0.00001703406,"domain_scores_codex":[0.9991868,0.00001760684,0.0002701679,0.0002019751,0.00008160853,0.0002418377],"domain_scores_gemma":[0.9993274,0.00009448976,0.00007819743,0.0004007632,0.00001784468,0.00008134036],"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":[0.00002613561,0.00001524669,0.001516058,0.0006387792,0.00004081926,7.638367e-7,0.00006321515,0.000127968,0.9931976,0.0004864444,0.000005376464,0.003881625],"study_design_scores_gemma":[0.000802492,0.00008182733,0.004383944,0.00004797505,0.00008134974,7.583631e-7,0.000008473095,0.00792759,0.9861691,0.000166476,0.0001364007,0.0001936031],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975654,0.00112961,0.0001521693,0.00003982738,0.0002023931,0.0005497505,0.00004805815,0.00006423753,0.0002485472],"genre_scores_gemma":[0.9985078,0.0004884902,0.00007997554,0.000003534227,0.00005188258,0.0007835192,0.00003366359,0.00003200887,0.00001914434],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007799622,"threshold_uncertainty_score":0.6626776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006136813852754558,"score_gpt":0.2147997666596769,"score_spread":0.2086629528069223,"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."}}