{"id":"W4309167129","doi":"10.1515/cclm-2022-0491","title":"Mucin 13 (MUC13) as a candidate biomarker for ovarian cancer detection: potential to complement CA125 in detecting non-serous subtypes","year":2022,"lang":"en","type":"article","venue":"Clinical Chemistry and Laboratory Medicine (CCLM)","topic":"Glycosylation and Glycoproteins Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; Lunenfeld-Tanenbaum Research Institute; University of Toronto; Mount Sinai Hospital","funders":"","keywords":"Ovarian cancer; Biomarker; Serous fluid; Medicine; Ovarian tumor; Internal medicine; Malignancy; Oncology; Cancer; Mucin; Pathology; Biology","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":[0.001697257,0.0005285975,0.000518362,0.001212039,0.0002139469,0.0006124481,0.0002926208,0.0004860462,0.001017679],"category_scores_gemma":[0.002143983,0.0001745329,0.000521595,0.001001603,0.0003150285,0.0003623485,0.0004307436,0.0003988595,0.0002560503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003419184,"about_ca_system_score_gemma":0.0004089306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001260579,"about_ca_topic_score_gemma":0.002038932,"domain_scores_codex":[0.9992868,0.0002626845,0.00006802725,0.0001250984,0.0001895591,0.00006783872],"domain_scores_gemma":[0.999,0.0002670631,0.0003553278,0.00005303468,0.0002004073,0.0001240666],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001621952,0.0001994062,0.7615091,0.000670529,0.0003368623,0.0004389149,0.0001064695,0.0009117411,0.1667396,0.0001363068,0.0004154802,0.06691369],"study_design_scores_gemma":[0.00007527207,0.00312893,0.8827112,0.0001451444,0.0004145495,0.004365088,0.0001670317,0.008384407,0.09648587,0.0002071428,0.003870357,0.00004513488],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9782841,0.01325847,0.006412815,0.0001613756,0.00004483636,0.0001173256,0.0005521969,0.0001042956,0.001064595],"genre_scores_gemma":[0.9897419,0.001328749,0.008069891,0.00007227204,0.00002586736,0.00003953619,0.0003503933,0.000006236816,0.0003651993],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001697257,"threshold_uncertainty_score":0.008976042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02928933173210178,"score_gpt":0.3739429556396345,"score_spread":0.3446536239075327,"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."}}