{"id":"W4388774038","doi":"10.1186/s40364-023-00540-2","title":"Extracellular vesicle-based liquid biopsy biomarkers and their application in precision immuno-oncology","year":2023,"lang":"en","type":"review","venue":"Biomarker Research","topic":"Extracellular vesicles in disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":92,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dr. Georges-L.-Dumont University Hospital Centre; Beatrice Hunter Cancer Research Institute; Université de Moncton; Atlantic Cancer Research Institute","funders":"Mitacs; Fondation de la recherche en santé du Nouveau-Brunswick","keywords":"Liquid biopsy; Tumor microenvironment; Extracellular vesicles; Biomarker; Extracellular vesicle; Circulating tumor cell; Cancer biomarkers; Medicine; Biomarker discovery; Microvesicles; Computational biology; Bioinformatics; Immune system; Cancer; Biology; Proteomics; Internal medicine; Immunology; Metastasis; Cell biology","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":[0.002071328,0.0005752715,0.0005821924,0.001246259,0.0002712728,0.001763304,0.0006744817,0.002260517,0.001648176],"category_scores_gemma":[0.002473021,0.0004002906,0.000490368,0.0008872101,0.0009874903,0.001694768,0.001206514,0.001555002,0.0008481963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009830788,"about_ca_system_score_gemma":0.0006426457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008423509,"about_ca_topic_score_gemma":0.0006900112,"domain_scores_codex":[0.9989801,0.0003524537,0.00003639057,0.0001839313,0.0003770211,0.0000699927],"domain_scores_gemma":[0.9990299,0.000410217,0.0001616667,0.00006756073,0.0002438661,0.00008687687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007695372,0.0002488389,0.004414222,0.003108547,0.0001987301,0.001548065,0.0004627576,0.007957463,0.3484904,0.06657769,0.01646388,0.5497598],"study_design_scores_gemma":[0.0001314029,0.001883352,0.004622903,0.001378992,0.000229953,0.004688378,0.0003907401,0.04215609,0.4823292,0.03009153,0.4317582,0.000339263],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.05923757,0.6280026,0.2764266,0.01153586,0.002244439,0.0005274925,0.0010402,0.0009442033,0.02004099],"genre_scores_gemma":[0.5293416,0.2778618,0.1736481,0.006180275,0.001133441,0.0007170639,0.0009014957,0.0001722388,0.01004388],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002260517,"threshold_uncertainty_score":0.01095432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1179422531171736,"score_gpt":0.4297581589310074,"score_spread":0.3118159058138338,"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."}}