{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005869361,0.0001348209,0.0002142763,0.00001301248,0.0001240271,0.00001119815,0.0001377086,0.0001197511,0.000134653],"category_scores_gemma":[0.001337651,0.00008990879,0.00005668121,0.000102802,0.001158843,0.000006465739,0.0001004701,0.0001118556,0.000001768518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003300012,"about_ca_system_score_gemma":0.000103317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001990056,"about_ca_topic_score_gemma":0.00000585235,"domain_scores_codex":[0.9988855,0.00007976995,0.0003472939,0.0003520491,0.0001497312,0.0001856421],"domain_scores_gemma":[0.9989991,0.0001170724,0.0001008028,0.0003203157,0.000260022,0.0002027313],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001466677,0.0001459168,0.02447861,0.0003393768,0.0001693902,0.000007358428,0.000120177,5.126396e-7,0.9534916,0.00006211379,0.00991103,0.009807227],"study_design_scores_gemma":[0.006594876,0.001997918,0.08768618,0.0001945523,0.0002171777,0.0000286811,0.001410698,0.0004174272,0.4842181,0.0003573091,0.4163958,0.0004812984],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962768,0.001633873,0.0001402202,0.0008791016,0.0001268268,0.000222352,0.0000745322,0.000008031962,0.0006382506],"genre_scores_gemma":[0.9973131,0.0003038232,0.00005040326,0.000555151,0.001200228,0.00004942478,0.00002946002,0.00001684579,0.0004815615],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4692735,"threshold_uncertainty_score":0.4269805,"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."}}