{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002614341,0.0005274626,0.0004796178,0.001225524,0.0002284694,0.0006713446,0.00046841,0.0003831727,0.000432528],"category_scores_gemma":[0.003018743,0.0001838641,0.0005570902,0.0007471954,0.0002951369,0.0004694954,0.0005551258,0.0003955011,0.0001537769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007125913,"about_ca_system_score_gemma":0.0006253247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002805157,"about_ca_topic_score_gemma":0.004219277,"domain_scores_codex":[0.999473,0.0002057605,0.00005014749,0.00008209013,0.0001260251,0.00006287133],"domain_scores_gemma":[0.9989039,0.0003105671,0.0002851055,0.0001068247,0.0002414468,0.0001521546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007972543,0.00002535971,0.9813741,0.00004814957,0.00009358488,0.00006135755,0.00004470545,0.0005458039,0.002470373,0.00006699081,0.000204377,0.01426795],"study_design_scores_gemma":[0.0000837646,0.0007895502,0.977421,0.0001114752,0.0004414994,0.001044283,0.0002913429,0.01001004,0.005831629,0.0008023435,0.003151777,0.00002133866],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9906207,0.005286871,0.001985006,0.000193689,0.00002407176,0.0000708336,0.0004863322,0.00003442548,0.00129811],"genre_scores_gemma":[0.9972329,0.0005628041,0.001616349,0.00003797071,0.00001241406,0.00002240834,0.0003558455,0.000004963338,0.0001543725],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002805157,"threshold_uncertainty_score":0.01382607,"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."}}