{"id":"W2149493878","doi":"10.1158/1055-9965.epi-07-0692","title":"BTF4/BTNA3.2 and GCS as Candidate mRNA Prognostic Markers in Epithelial Ovarian Cancer","year":2008,"lang":"en","type":"article","venue":"Cancer Epidemiology Biomarkers & Prevention","topic":"RNA modifications and cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; McGill University Health Centre; Immunovaccine (Canada); Centre Hospitalier de l’Université de Montréal","funders":"","keywords":"Serous fluid; Ovarian cancer; Microarray; Oncology; Proportional hazards model; Internal medicine; Hazard ratio; Microarray analysis techniques; Cancer; Biology; Univariate analysis; Gene; Medicine; Multivariate analysis; Gene expression; Confidence interval; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009451407,0.0002825705,0.0003872214,0.0001307332,0.0001966012,0.000008973418,0.0002054243,0.0003622437,0.0001693092],"category_scores_gemma":[0.0003246685,0.0002749893,0.0001359353,0.0002024289,0.0004058015,0.0000188831,0.00009353866,0.0001758097,0.00001099996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001273781,"about_ca_system_score_gemma":0.0004090167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003119234,"about_ca_topic_score_gemma":0.002033764,"domain_scores_codex":[0.9974376,0.0005542003,0.0005875861,0.00079211,0.00009515834,0.0005333687],"domain_scores_gemma":[0.998978,0.00008161706,0.0002971506,0.0003914933,0.00008333125,0.0001684025],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00103571,0.0001233956,0.8721434,0.00006737244,0.0005040948,0.00001779042,0.0001138255,0.0001948369,0.06142566,0.0002730208,0.01202021,0.05208067],"study_design_scores_gemma":[0.00242938,0.0003432709,0.9468784,0.0002090806,0.0001259622,0.00008356141,0.0000866537,0.000486318,0.005207367,0.001867053,0.04168252,0.0006004082],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9714777,0.02316851,0.001023182,0.002520755,0.0006186523,0.0006387916,0.00006687794,0.00002425789,0.0004612017],"genre_scores_gemma":[0.9679613,0.02713228,0.0009283815,0.0007896678,0.0003213846,0.0008365986,0.0002219241,0.00003729253,0.001771159],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07473502,"threshold_uncertainty_score":0.9999703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03164686023775176,"score_gpt":0.3315794490885057,"score_spread":0.299932588850754,"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."}}