{"id":"W4402813080","doi":"10.1016/j.jmoldx.2024.09.001","title":"Improving Specificity for Ovarian Cancer Screening Using a Novel Extracellular Vesicle–Based Blood Test","year":2024,"lang":"en","type":"article","venue":"Journal of Molecular Diagnostics","topic":"Extracellular vesicles in disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; BC Cancer Agency","funders":"Common Fund; NIH Office of the Director; National Heart, Lung, and Blood Institute; National Institute of Mental Health; Medical Research Council; Ovarian Cancer Canada; National Cancer Institute; National Institutes of Health; Oak Foundation","keywords":"Ovarian cancer; Cohort; Extracellular vesicles; Test (biology); Medicine; Extracellular vesicle; Oncology; Internal medicine; Cancer; Biology; Microvesicles; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006048194,0.000299086,0.0002901065,0.0001663271,0.0001120182,0.000182521,0.000389028,0.0002200024,0.00002051753],"category_scores_gemma":[0.002032045,0.0003041836,0.0004576354,0.0002114096,0.00009709872,0.00001884518,0.00009710957,0.0003034364,9.390972e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006102781,"about_ca_system_score_gemma":0.0005698584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001552521,"about_ca_topic_score_gemma":0.000004014186,"domain_scores_codex":[0.9980743,0.00005420924,0.0006677339,0.0004052194,0.0003793327,0.000419207],"domain_scores_gemma":[0.9982983,0.0002961245,0.000369673,0.000376405,0.0003982373,0.000261275],"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":[0.00008749541,0.000378759,0.001074139,0.0002067467,0.0002533219,0.000487139,0.00001552465,0.009684451,0.984002,0.0002375188,0.0002328755,0.003340052],"study_design_scores_gemma":[0.001692193,0.0005010734,0.0001849179,0.000501674,0.0009783701,0.0001966525,0.00003785841,0.03454278,0.9526767,0.0001366196,0.008118323,0.0004328699],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3390037,0.02861005,0.6314436,0.00014482,0.0003940291,0.0002373842,0.0001391423,0.00001304656,0.00001419746],"genre_scores_gemma":[0.8535935,0.0002536851,0.1446775,0.0002027473,0.001078687,0.00001472461,0.00003128134,0.0001136981,0.00003417915],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5145897,"threshold_uncertainty_score":0.9999411,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01961417599268327,"score_gpt":0.2803187748243439,"score_spread":0.2607045988316606,"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."}}