{"id":"W1969698372","doi":"10.1245/s10434-010-0954-y","title":"Micrometastatic Node-Positive Breast Cancer: Long-Term Outcomes and Identification of High-Risk Subsets in a Large Population-Based Series","year":2010,"lang":"en","type":"article","venue":"Annals of Surgical Oncology","topic":"Breast Cancer Treatment Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; University of Victoria; BC Cancer Agency","funders":"","keywords":"Medicine; Breast cancer; Oncology; Internal medicine; Proportional hazards model; Lymphovascular invasion; Lymph node; Recursive partitioning; Population; Surgical oncology; Prognostic variable; Stage (stratigraphy); Cancer; Survival analysis; Cancer registry; Gynecology; Metastasis; 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":[0.0007285578,0.0003338493,0.0005822884,0.0009783272,0.0008334995,0.0008961855,0.0005040056,0.0004997453,0.001204849],"category_scores_gemma":[0.002016725,0.0004781995,0.0005546313,0.001421383,0.0005791765,0.001006491,0.0006667903,0.0007005141,0.0002288682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003747765,"about_ca_system_score_gemma":0.0004225023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004789972,"about_ca_topic_score_gemma":0.00638237,"domain_scores_codex":[0.9993845,0.0002137266,0.00007004147,0.0001618272,0.00008264929,0.00008720668],"domain_scores_gemma":[0.9987459,0.000298804,0.0003383166,0.0001829237,0.0001293588,0.0003045336],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001915888,0.00004200075,0.9987673,0.000003674873,0.00006337086,0.00008837175,0.00008342401,0.00001746769,0.000258833,0.000008700719,0.00003131036,0.000444004],"study_design_scores_gemma":[0.00001251095,0.0001336957,0.9988282,0.000002193974,0.00005770434,0.0003589797,0.0003635116,0.00007424557,0.00006361222,0.00001824428,0.00008246263,0.000004522949],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996213,0.0001442852,0.0000328823,0.00001598791,0.000002774766,0.000002572807,0.00008457048,9.083859e-7,0.0000946823],"genre_scores_gemma":[0.9995932,0.0001022163,0.00002074645,0.00001223634,0.00001012557,0.000004546239,0.0001757802,0.000001324929,0.00007989342],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004789972,"threshold_uncertainty_score":0.009524167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0154076642895427,"score_gpt":0.3301358664637331,"score_spread":0.3147282021741903,"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."}}