{"id":"W3125409058","doi":"10.1039/d0nr05525e","title":"Nanoscale flow cytometry for immunophenotyping and quantitating extracellular vesicles in blood plasma","year":2021,"lang":"en","type":"article","venue":"Nanoscale","topic":"Extracellular vesicles in disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver Biotech (Canada); University of British Columbia","funders":"Congressionally Directed Medical Research Programs; Michael Smith Health Research BC; Natural Sciences and Engineering Research Council of Canada; U.S. Department of Defense","keywords":"Flow cytometry; Extracellular vesicles; Immunophenotyping; Nanoscopic scale; Microvesicles; Chemistry; Cytometry; Plasma; Nanotechnology; Materials science; Molecular biology; Biology; Cell biology; Biochemistry; Physics; microRNA","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":[0.001039579,0.0006436546,0.0005732248,0.001819646,0.000516688,0.000849716,0.000544414,0.001259047,0.003690904],"category_scores_gemma":[0.0008198313,0.0002781391,0.0004338645,0.0007919937,0.0003908035,0.0006185212,0.0004782995,0.001053795,0.001531917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005475922,"about_ca_system_score_gemma":0.000288083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004527789,"about_ca_topic_score_gemma":0.0006168287,"domain_scores_codex":[0.999,0.0002162693,0.00009222494,0.0003185144,0.0002869153,0.00008613009],"domain_scores_gemma":[0.9995449,0.0002064678,0.00006809078,0.00004818975,0.0001053035,0.00002697534],"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":[0.00008589833,0.0000656124,0.0007129839,0.0001308435,0.00001208468,0.00003934828,0.00005466157,0.000229715,0.9869769,0.0007855365,0.0005277762,0.01037863],"study_design_scores_gemma":[0.00003009654,0.0003606087,0.006839255,0.00008031685,0.00003953648,0.000461973,0.00008556651,0.01915694,0.9583142,0.001424704,0.01316383,0.0000430136],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2373138,0.00692104,0.7343609,0.0007986823,0.0006203225,0.001011208,0.004182494,0.004128231,0.01066337],"genre_scores_gemma":[0.374313,0.006814105,0.5973887,0.0009801546,0.000364046,0.003960426,0.005287217,0.0004341374,0.01045818],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003690904,"threshold_uncertainty_score":0.01234728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01162589422582514,"score_gpt":0.2528794605862053,"score_spread":0.2412535663603802,"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."}}