{"id":"W2969651887","doi":"10.1016/j.clbc.2019.06.013","title":"Impact of NCI Socioeconomic Index on the Outcomes of Nonmetastatic Breast Cancer Patients: Analysis of SEER Census Tract–Level Socioeconomic Database","year":2019,"lang":"en","type":"article","venue":"Clinical Breast Cancer","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":54,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Medicine; Socioeconomic status; Breast cancer; Hazard ratio; Proportional hazards model; Demography; Epidemiology; Confidence interval; Cancer registry; Cohort; Cancer; Multivariate analysis; Oncology; Gynecology; Gerontology; Internal medicine; Population; Environmental health","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":[0.001491342,0.0002578131,0.0004689477,0.001099884,0.0003160148,0.0009267557,0.0005049497,0.0003153695,0.002261019],"category_scores_gemma":[0.005483174,0.0001730928,0.001386328,0.002352674,0.0002032102,0.0006608183,0.001233464,0.0006282572,0.0002848537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006005318,"about_ca_system_score_gemma":0.0007247784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02295295,"about_ca_topic_score_gemma":0.03415599,"domain_scores_codex":[0.9987773,0.0003947736,0.0001542938,0.0002048172,0.0002517349,0.0002170117],"domain_scores_gemma":[0.9971784,0.0006643656,0.001177344,0.0003105338,0.000323857,0.0003455138],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001379726,0.00001602328,0.9984382,0.000008066231,0.0002570953,0.00001888449,0.00001738145,0.00007519512,0.00002945995,0.00002364971,0.0002900431,0.0006880444],"study_design_scores_gemma":[0.000003752163,0.000021553,0.9993093,0.000003359853,0.00005854216,0.00003287938,0.00008249345,0.0003017877,0.00001387642,0.00001736931,0.0001526042,0.000002548068],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9896277,0.0003318631,0.00008648246,0.0002154073,0.00001697952,0.000009508313,0.008495732,0.000006209948,0.001210149],"genre_scores_gemma":[0.9945148,0.0001077357,0.00003570838,0.00004244763,0.00001075199,0.000006042062,0.005088211,0.000003897144,0.0001902752],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02295295,"threshold_uncertainty_score":0.04563868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09886965925997132,"score_gpt":0.4275932679825297,"score_spread":0.3287236087225584,"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."}}