{"id":"W2969983976","doi":"10.1039/c9an00777f","title":"Exosome-specific tumor diagnosis<i>via</i>biomedical analysis of exosome-containing microRNA biomarkers","year":2019,"lang":"en","type":"article","venue":"The Analyst","topic":"Extracellular vesicles in disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Infection and Immunity","funders":"Science and Technology Bureau, Guiyang Municipal Government; National Natural Science Foundation of China","keywords":"Exosome; Microvesicles; microRNA; Computational biology; Liquid biopsy; Cancer research; Medicine; Chemistry; Biology; Cancer; Gene; Biochemistry; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005739576,0.0002345205,0.0004461209,0.000276196,0.00008258167,0.00002939141,0.0007303376,0.000113486,0.0003674133],"category_scores_gemma":[0.00005782776,0.0001811602,0.0006147478,0.001116034,0.0003520058,0.000006764535,0.0002408955,0.0001267629,0.00008257246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002714823,"about_ca_system_score_gemma":0.00005893301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005343178,"about_ca_topic_score_gemma":0.00003688598,"domain_scores_codex":[0.9980758,0.0001893526,0.0005102936,0.0005226586,0.000339474,0.000362431],"domain_scores_gemma":[0.99814,0.00008821322,0.0002908033,0.001218684,0.00009996512,0.0001623135],"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":[0.0002117151,0.0001953609,0.08972483,0.0000248645,0.003429434,0.00002089344,0.00008578868,0.0001284798,0.902649,0.00008384449,0.001831214,0.0016146],"study_design_scores_gemma":[0.003036859,0.0008359837,0.1645001,0.0001027175,0.006980252,0.00003985781,0.001689151,0.003493031,0.6877494,0.0002724137,0.1298305,0.001469694],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930227,0.004287021,0.001369441,0.0002281187,0.0001254819,0.0002155453,0.00006645355,0.0000155046,0.0006697058],"genre_scores_gemma":[0.9982786,0.0002401664,0.0003632122,0.0002942317,0.0001383199,0.00002824688,0.0003430129,0.00003136901,0.0002828618],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2148996,"threshold_uncertainty_score":0.73875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007957778394857439,"score_gpt":0.2347002236221157,"score_spread":0.2267424452272582,"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."}}