{"id":"W4402690342","doi":"10.1039/d4nr00729h","title":"Investigating nano-sized tumor-derived extracellular vesicles in enhancing anti-PD-1 immunotherapy","year":2024,"lang":"en","type":"article","venue":"Nanoscale","topic":"Extracellular vesicles in disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"University of Waterloo; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Extracellular vesicles; Immunotherapy; Nano-; Vesicle; Extracellular; Nanotechnology; Immune system; Materials science; Chemistry; Immunology; Medicine; Cell biology; Biology; Biochemistry; Membrane; Composite material","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002386436,0.000190845,0.0002159478,0.0001396956,0.0001010525,0.0004114125,0.0001751255,0.0003863119,0.0003235173],"category_scores_gemma":[0.0001810478,0.0001050344,0.0002081334,0.00009047362,0.0001695858,0.0004566538,0.0002540992,0.000345205,0.0001416439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003318081,"about_ca_system_score_gemma":0.0001579297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003474546,"about_ca_topic_score_gemma":0.0004378874,"domain_scores_codex":[0.9998903,0.00002233347,0.000005848072,0.0000250291,0.0000311463,0.00002538831],"domain_scores_gemma":[0.9999475,0.00001823135,0.00001375138,0.000003694737,0.000007902524,0.000008949713],"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":[0.0001166609,0.00008412093,0.0001806168,0.0002019,0.00001208885,0.00006959566,0.0000295401,0.002386251,0.9880669,0.001462349,0.0001991026,0.007190828],"study_design_scores_gemma":[0.00003332045,0.0005596869,0.0007021198,0.00001773875,0.00002286217,0.00009298015,0.00003436737,0.02086799,0.9706619,0.0003025819,0.006689086,0.00001532274],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9647512,0.00864558,0.02174378,0.0004164973,0.0001427178,0.0001477213,0.0001805174,0.0001027231,0.00386933],"genre_scores_gemma":[0.9880679,0.002263848,0.008303584,0.00009586275,0.00001402188,0.0000744991,0.000067991,0.0000158956,0.001096413],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0004114125,"threshold_uncertainty_score":0.002407432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009418980933982442,"score_gpt":0.2518041895680955,"score_spread":0.242385208634113,"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."}}