{"id":"W2804860120","doi":"10.1515/cclm-2018-0139","title":"Exploring the potential of mucin 13 (MUC13) as a biomarker for carcinomas and other diseases","year":2018,"lang":"en","type":"article","venue":"Clinical Chemistry and Laboratory Medicine (CCLM)","topic":"Glycosylation and Glycoproteins Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital; University of Toronto; University Health Network","funders":"","keywords":"Biomarker; Cancer; Medicine; Immunology; Autoantibody; Lung cancer; Melanoma; Mucin; Cancer research; Pathology; Antibody; Internal medicine; 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":[0.001644475,0.000454379,0.00038723,0.001425629,0.0002158055,0.0008780538,0.0003416885,0.0006190703,0.0008337522],"category_scores_gemma":[0.001390059,0.0001403278,0.0004678236,0.001019486,0.0004137486,0.000610943,0.0004628707,0.0005128515,0.0002363347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000398765,"about_ca_system_score_gemma":0.0005016838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005866871,"about_ca_topic_score_gemma":0.0005148997,"domain_scores_codex":[0.9996444,0.000146655,0.00002939013,0.00005365661,0.00006955704,0.0000562376],"domain_scores_gemma":[0.9991912,0.0002681443,0.0002167285,0.00004306772,0.000162702,0.0001180663],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001459681,0.0002457361,0.6409481,0.001110362,0.000367781,0.0009806624,0.0002006665,0.0007481683,0.2443303,0.0006529201,0.0009075649,0.1080481],"study_design_scores_gemma":[0.0001072512,0.005046914,0.7116113,0.0005172351,0.001068003,0.009627962,0.0009343298,0.007024162,0.2355594,0.002412876,0.02599832,0.00009226127],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9482927,0.04285244,0.005677873,0.0008277337,0.00007726198,0.00007825007,0.000352708,0.00007762077,0.00176343],"genre_scores_gemma":[0.9845759,0.008052171,0.006325827,0.0002910232,0.00007149775,0.00003967104,0.0002352545,0.000009249739,0.0003994133],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001644475,"threshold_uncertainty_score":0.008696914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08575976530073619,"score_gpt":0.3719280470788721,"score_spread":0.2861682817781359,"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."}}