{"id":"W2981254457","doi":"10.1200/jco.2007.25.18_suppl.10582","title":"Can we identify a group of breast cancer patients with a good prognosis despite four or more positive (4+) axillary nodes using a tissue microarray (TMA)?","year":2007,"lang":"en","type":"article","venue":"Journal of Clinical Oncology","topic":"Breast Cancer Treatment Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency","funders":"","keywords":"Medicine; Breast cancer; Internal medicine; Oncology; Biomarker; Axillary lymph nodes; Immunohistochemistry; Proportional hazards model; Univariate analysis; Estrogen receptor; Tissue microarray; Stage (stratigraphy); Cancer; Pathology; Multivariate analysis","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":[0.0006634106,0.0003077219,0.0005715279,0.0009947954,0.0002484091,0.0006141886,0.0004253168,0.000639721,0.001559705],"category_scores_gemma":[0.003209049,0.000150276,0.0003025655,0.0005446261,0.0002481847,0.0007507199,0.0003321094,0.0002096271,0.0008208221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001887559,"about_ca_system_score_gemma":0.0002576023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007497686,"about_ca_topic_score_gemma":0.001574321,"domain_scores_codex":[0.999716,0.00006744177,0.00003120151,0.00008300005,0.00004775214,0.00005450538],"domain_scores_gemma":[0.9990181,0.0003061461,0.0002680186,0.0001065459,0.0001335121,0.000167632],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005235784,0.00004258886,0.9814099,0.00002939249,0.00003178335,0.0002250913,0.00007596442,0.0001730106,0.002138953,0.00002904325,0.0004122524,0.0149084],"study_design_scores_gemma":[0.00003879175,0.0003508517,0.9930632,0.00002359955,0.00008964563,0.001237863,0.0004615253,0.002973637,0.0005233074,0.0004150247,0.0008061843,0.00001641958],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983402,0.0002533575,0.0005172037,0.0002467491,0.00001806412,0.00001659749,0.0002330995,0.00001330762,0.000361453],"genre_scores_gemma":[0.9983039,0.0001257411,0.0008469524,0.00009110374,0.00004176383,0.00003330811,0.0004468488,0.000003062048,0.0001071734],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001559705,"threshold_uncertainty_score":0.005217731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04671597237235373,"score_gpt":0.4111796573106953,"score_spread":0.3644636849383415,"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."}}