{"id":"W4205397379","doi":"10.1016/j.neo.2021.12.008","title":"RNA biomarkers from proximal liquid biopsy for diagnosis of ovarian cancer","year":2022,"lang":"en","type":"article","venue":"Neoplasia","topic":"Ovarian cancer diagnosis and treatment","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Bijzonder Onderzoeksfonds UGent; Universiteit Gent; Tel Aviv University; Israel Cancer Research Fund; Israel Science Foundation; Fonds De La Recherche Scientifique - FNRS; Kom op tegen Kanker; Israel Cancer Association; Fonds Wetenschappelijk Onderzoek","keywords":"Liquid biopsy; Ovarian cancer; RNA; RNA extraction; Biopsy; Oncology; Biomarker; Medicine; Internal medicine; microRNA; Cancer research; Biology; Pathology; Computational biology; Cancer; Gene; Genetics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001053669,0.0001654597,0.0003636461,0.0001029393,0.0001305537,0.000009198267,0.0001063578,0.00005537823,0.002530484],"category_scores_gemma":[0.00003120565,0.0001507394,0.00019372,0.0002487589,0.00004466929,0.0000388521,0.00007016819,0.0001001841,0.000005647898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002843861,"about_ca_system_score_gemma":0.0002968006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002165462,"about_ca_topic_score_gemma":0.00008567188,"domain_scores_codex":[0.9987742,0.00003371128,0.0002820662,0.0003711912,0.0002861938,0.0002526141],"domain_scores_gemma":[0.9991875,0.0001680897,0.000143946,0.0003137141,0.00006452156,0.0001222883],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01111122,0.003697672,0.7909887,0.0003643012,0.004114561,0.0001927576,0.001887599,0.00008170444,0.01148741,0.001569992,0.09696255,0.07754156],"study_design_scores_gemma":[0.02586288,0.008656152,0.4051665,0.0004630089,0.002800603,0.00008623026,0.001061259,0.0005075145,0.1997057,0.0004829004,0.3544207,0.0007864727],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9849918,0.002168674,0.00004802029,0.007182449,0.0007778991,0.001290396,0.001827297,0.00005237962,0.00166112],"genre_scores_gemma":[0.9918076,0.0001928367,0.002558336,0.0004622757,0.000238148,0.004356853,0.0001849645,0.00004001161,0.0001589869],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3858221,"threshold_uncertainty_score":0.9983813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02002322177797796,"score_gpt":0.2836421762548822,"score_spread":0.2636189544769043,"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."}}