{"id":"W4401503589","doi":"10.1016/j.canlet.2024.217184","title":"Extracellular vesicle-derived biomarkers in prostate cancer care: Opportunities and challenges","year":2024,"lang":"en","type":"review","venue":"Cancer Letters","topic":"Extracellular vesicles in disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Department of Medicine, School of Medicine, Queen's University; Ministry of Defence, Singapore; Consumer Programme; Ministry of Education - Singapore; National Research Foundation Singapore; National Health and Medical Research Council; Ministry of Health -Singapore; Center for Cancer Research","keywords":"Prostate cancer; Liquid biopsy; Extracellular vesicles; Biomarker; Extracellular vesicle; Medicine; Cancer biomarkers; Transformative learning; Disease; Biomarker discovery; Cancer; Oncology; Bioinformatics; Microvesicles; Internal medicine; Biology; Psychology; microRNA","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002158966,0.0007279835,0.001930833,0.001227687,0.00029429,0.002037527,0.001022708,0.002476486,0.002820705],"category_scores_gemma":[0.002580239,0.0002583173,0.0006208334,0.001335714,0.001039939,0.002317596,0.001145947,0.004358712,0.001643256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001195342,"about_ca_system_score_gemma":0.001745541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001493125,"about_ca_topic_score_gemma":0.002919777,"domain_scores_codex":[0.9995541,0.0001418883,0.00004110235,0.00005970362,0.0001527511,0.00005043646],"domain_scores_gemma":[0.9984348,0.0009920121,0.00009723415,0.00003060609,0.0003489613,0.0000963322],"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":[0.0001595407,0.0000743665,0.0002689335,0.006893134,0.00009255997,0.0002067611,0.00005128092,0.0005286374,0.001315552,0.01372902,0.06680334,0.9098769],"study_design_scores_gemma":[0.00004624526,0.0001317935,0.0006206568,0.004617966,0.00009209043,0.0007233723,0.0001025879,0.0003369457,0.0004207345,0.007370165,0.9855058,0.00003157456],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00004220798,0.997666,0.0001300798,0.001445048,0.0003783559,0.000001587567,0.000009534544,0.000004308114,0.0003228752],"genre_scores_gemma":[0.0006054364,0.9971448,0.0002000225,0.0009387625,0.0007683721,0.00000559281,0.00001730842,0.000001543861,0.0003182632],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002820705,"threshold_uncertainty_score":0.01141787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06751510810418593,"score_gpt":0.3200540842940903,"score_spread":0.2525389761899044,"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."}}