{"id":"W2544530174","doi":"10.1158/0008-5472.can-15-3231","title":"Enhanced Detection of Cancer Biomarkers in Blood-Borne Extracellular Vesicles Using Nanodroplets and Focused Ultrasound","year":2016,"lang":"en","type":"article","venue":"Cancer Research","topic":"Extracellular vesicles in disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research","keywords":"Extracellular vesicle; HT1080; Extracellular; Biology; Fibrosarcoma; Sonication; Vesicle; Extracellular vesicles; Cancer research; Molecular biology; Microvesicles; Cell biology; Chemistry; Biochemistry; microRNA; Gene; Genetics","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":[0.0003781338,0.0003272029,0.0002997363,0.0003177189,0.0001413222,0.0004222435,0.0002672756,0.0006377654,0.000349925],"category_scores_gemma":[0.0003890334,0.0002214635,0.0003242815,0.0001446213,0.0003090668,0.0004293085,0.0004196533,0.0005072728,0.0002595294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004610566,"about_ca_system_score_gemma":0.0001859176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000519465,"about_ca_topic_score_gemma":0.0006514613,"domain_scores_codex":[0.9997562,0.00005401978,0.0000170966,0.00006011648,0.00008788503,0.00002483748],"domain_scores_gemma":[0.9997897,0.00009142354,0.0000540049,0.00001389142,0.00003456759,0.00001654866],"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":[0.00001723244,0.000005112729,0.00006574727,0.00002325271,0.000002330147,0.00001888326,0.0000157179,0.00007830649,0.9985579,0.00008085456,0.0000161185,0.001118468],"study_design_scores_gemma":[0.000004432904,0.0000687559,0.0004371337,0.000003392369,0.000004843313,0.00004968964,0.00000880062,0.001217933,0.9976326,0.00004068698,0.0005269158,0.000004781918],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9355908,0.00445286,0.05740859,0.0003458302,0.00008376149,0.0001532209,0.0002862757,0.0002242961,0.001454458],"genre_scores_gemma":[0.9335732,0.002616602,0.06002308,0.0002386216,0.00003911044,0.0002121343,0.0002514271,0.00005519707,0.002990625],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006377654,"threshold_uncertainty_score":0.003345191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0305685347699926,"score_gpt":0.3439535922335131,"score_spread":0.3133850574635205,"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."}}