{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002622133,0.0001844197,0.0001972431,0.0006589662,0.0001266583,0.0002751715,0.0000960045,0.0002245232,0.0005771054],"category_scores_gemma":[0.0004794277,0.00007761016,0.0001030143,0.0003479905,0.0001785067,0.0001164266,0.000106147,0.0001784931,0.0001139559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002600203,"about_ca_system_score_gemma":0.0001661652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008030766,"about_ca_topic_score_gemma":0.001554129,"domain_scores_codex":[0.9999121,0.00002372651,0.000004144096,0.00001274044,0.00002815184,0.00001907909],"domain_scores_gemma":[0.9998424,0.00004948464,0.00005755662,0.000006633979,0.00002037416,0.00002344606],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00398029,0.0001385203,0.6473073,0.0001380004,0.0001217378,0.0004088568,0.0001113311,0.001560176,0.2702009,0.0001538661,0.0004652902,0.07541363],"study_design_scores_gemma":[0.0001268959,0.001191235,0.9411665,0.00002006976,0.0001126161,0.001113993,0.0001832123,0.00463628,0.04830284,0.0004146178,0.002714336,0.00001728044],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970796,0.001909217,0.0004911536,0.0000722358,0.00000757683,0.000007116511,0.0001731557,0.00001413783,0.0002458324],"genre_scores_gemma":[0.9980819,0.0003335975,0.0008913588,0.00002189857,0.00001322345,0.00001029524,0.0003170842,0.000002202444,0.0003284212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008030766,"threshold_uncertainty_score":0.001930594,"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."}}