{"id":"W4401911765","doi":"10.1021/acs.biomac.4c00535","title":"Scalable Purification, Storage, and Release of Plant-Derived Nanovesicles for Local Therapy Using Nanostructured All-Cellulose Composite Membranes","year":2024,"lang":"en","type":"article","venue":"Biomacromolecules","topic":"Polysaccharides and Plant Cell Walls","field":"Agricultural and Biological Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Kvantum-instituutti, Oulun Yliopisto; Academy of Finland","keywords":"Membrane; Cellulose; Chemical engineering; Filtration (mathematics); Composite number; Chemistry; Matrix (chemical analysis); Biocompatible material; Chromatography; Materials science; Nanotechnology; Organic chemistry; Biomedical engineering; Biochemistry; Composite material","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001848448,0.0003597745,0.0002159638,0.0001518654,0.0001329584,0.0002691066,0.0001474316,0.0003309762,0.0003992651],"category_scores_gemma":[0.0001375516,0.0001166544,0.000279969,0.00009381423,0.0001349825,0.0004413962,0.0003358742,0.0004951806,0.0001843831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002915732,"about_ca_system_score_gemma":0.0002268893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003146977,"about_ca_topic_score_gemma":0.0005986802,"domain_scores_codex":[0.9999188,0.000009979717,0.000006841047,0.00002032322,0.00002646581,0.00001762687],"domain_scores_gemma":[0.9999257,0.0000118078,0.00002718418,0.000008638219,0.00001332842,0.00001327602],"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":[0.000008595885,0.000004908729,0.00001899149,0.00002257133,0.000002116141,0.00001489315,0.000006367453,0.00006881533,0.9987702,0.0000451705,0.00001322171,0.001024164],"study_design_scores_gemma":[0.000003014014,0.00003699938,0.0002233364,0.000003706098,0.000004450076,0.00004331255,0.000009504782,0.0009961991,0.9978057,0.00003024214,0.000840184,0.000003462383],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9388689,0.004275728,0.05376855,0.0002133568,0.00006987841,0.0000981656,0.0002224784,0.0002447727,0.002238222],"genre_scores_gemma":[0.9738299,0.00228836,0.02203339,0.0000980431,0.00001409853,0.00008782745,0.0001406286,0.0000429384,0.001464761],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0003992651,"threshold_uncertainty_score":0.002115488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02571385483990524,"score_gpt":0.2331349273058443,"score_spread":0.2074210724659391,"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."}}