{"id":"W2970781240","doi":"10.1016/j.neo.2019.07.011","title":"MCM2, MCM4, and MCM6 in Breast Cancer: Clinical Utility in Diagnosis and Prognosis","year":2019,"lang":"en","type":"article","venue":"Neoplasia","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":122,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Research in Immunology and Cancer; Université de Montréal","funders":"University of California, Santa Cruz","keywords":"Tissue microarray; Breast cancer; Oncology; Triple-negative breast cancer; Immunohistochemistry; Internal medicine; Medicine; Cancer; Cancer research; Pathology","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":[0.0002098353,0.00009804094,0.0001484222,0.0000437494,0.00001719349,0.00001618377,0.00006900459,0.0001686498,0.00005966874],"category_scores_gemma":[0.00001917051,0.00009141421,0.00002620489,0.00009651726,0.0000545337,0.000005338182,0.0000738794,0.0001120901,0.000004154451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001081332,"about_ca_system_score_gemma":0.00005769974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001486274,"about_ca_topic_score_gemma":0.0005687388,"domain_scores_codex":[0.9990655,0.00007975406,0.0002241928,0.0004107188,0.00006992875,0.0001499678],"domain_scores_gemma":[0.9996508,0.00002024769,0.0000536481,0.00018197,0.00002266169,0.00007071093],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009041581,0.00008043923,0.9370647,0.00002309899,0.000005188409,7.956658e-7,0.00003969945,0.000001295063,0.008621185,0.00001118077,0.001257688,0.05280431],"study_design_scores_gemma":[0.0008812603,0.00006199189,0.9754291,0.00004255574,0.000004333287,0.000005667686,0.00009206398,0.0001248939,0.00450277,0.00002143489,0.01873014,0.0001037683],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968728,0.001192248,0.000003797454,0.001081856,0.0001302214,0.0002425323,0.00001924083,0.00000512827,0.0004521708],"genre_scores_gemma":[0.9947599,0.004598656,0.00005574396,0.0002599141,0.00005776382,0.0001264656,0.00001331968,0.000008844919,0.0001193897],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05270055,"threshold_uncertainty_score":0.3727763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01795519356548136,"score_gpt":0.3088390735399279,"score_spread":0.2908838799744465,"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."}}