{"id":"W4365515854","doi":"10.3389/fonc.2023.1134763","title":"GD2 and GD3 gangliosides as diagnostic biomarkers for all stages and subtypes of epithelial ovarian cancer","year":2023,"lang":"en","type":"article","venue":"Frontiers in Oncology","topic":"Glycosylation and Glycoproteins Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Centre Hospitalier de l’Université de Montréal; McGill University; Jewish General Hospital","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Ovarian Cancer Canada; Réseau Québécois de Recherche sur les Médicaments","keywords":"Medicine; Ovarian cancer; Stage (stratigraphy); Cancer; Internal medicine; Epithelial ovarian cancer; Cohort; Immunohistochemistry; Retrospective cohort study; Pathology; Diagnostic biomarker; Oncology; Gastroenterology; Biology","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":[],"consensus_categories":[],"category_scores_codex":[0.0002899589,0.00008380777,0.0001697525,0.0001539616,0.00003468042,0.00000814009,0.00007793403,0.0001646715,0.00001589028],"category_scores_gemma":[0.0006759395,0.00008039969,0.00002636877,0.0001182547,0.0001829722,0.000003574048,0.00007623055,0.00005202951,0.000001338066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002123439,"about_ca_system_score_gemma":0.0001068319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002369284,"about_ca_topic_score_gemma":0.0004025384,"domain_scores_codex":[0.9992609,0.00007278194,0.0001477363,0.0002361218,0.0000637682,0.0002187085],"domain_scores_gemma":[0.9996219,0.0001165237,0.00004950215,0.000103161,0.0000465977,0.00006226858],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002669786,0.0001434479,0.3938258,0.0003240154,0.0003863998,0.00006459119,0.0007249128,0.0001083149,0.3764389,0.000422403,0.09200304,0.1328884],"study_design_scores_gemma":[0.007512832,0.003713545,0.2056499,0.00006547066,0.00007853689,0.00002587087,0.001325927,0.001312691,0.2763568,0.005062824,0.4983641,0.0005315786],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994202,0.002833736,0.0003887776,0.001442209,0.0003084968,0.0004468103,0.00009301068,0.000008215159,0.0002767725],"genre_scores_gemma":[0.9929588,0.003625779,0.002240317,0.0001665567,0.00008206548,0.0001687214,0.0000706931,0.00001586024,0.0006711485],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.406361,"threshold_uncertainty_score":0.3278604,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01491588538026007,"score_gpt":0.3278000166196475,"score_spread":0.3128841312393874,"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."}}