{"id":"W2759862632","doi":"10.1016/j.ijrobp.2017.06.1590","title":"What Explains Variation in Medical Spending for Patients With Breast Cancer?","year":2017,"lang":"en","type":"article","venue":"International Journal of Radiation Oncology*Biology*Physics","topic":"Economic and Financial Impacts of Cancer","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Medicine; Breast cancer; Lumpectomy; Mastectomy; Cancer; Disease; Comorbidity; Demography; Internal medicine","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":[0.001876448,0.0002444238,0.0006246982,0.001021907,0.0004718402,0.001418893,0.0008187419,0.00142193,0.004451764],"category_scores_gemma":[0.01944003,0.00033181,0.001401329,0.002549655,0.0006578477,0.0007085358,0.0007793947,0.001375305,0.0004701927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001368085,"about_ca_system_score_gemma":0.001236197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0340622,"about_ca_topic_score_gemma":0.03790208,"domain_scores_codex":[0.9980356,0.0008334196,0.0001548307,0.0003198636,0.0001304207,0.0005259219],"domain_scores_gemma":[0.9821334,0.009502469,0.004763075,0.001163638,0.000629225,0.001808296],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000115164,0.00005279862,0.994803,0.00001464521,0.0003923876,0.00007477093,0.0001057985,0.000689535,0.00004449263,0.0003352871,0.0008431248,0.002528893],"study_design_scores_gemma":[0.00001149855,0.00002735396,0.995917,0.00002261971,0.0001021175,0.0001274461,0.0004183034,0.001901265,0.00003307734,0.0008010587,0.0006295895,0.000008615091],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910548,0.001448632,0.0003280869,0.004314709,0.00007012125,0.000006522715,0.001343643,0.000009975676,0.00142349],"genre_scores_gemma":[0.9989292,0.0001473008,0.00006129435,0.0001750807,0.00004172193,0.000003511615,0.0004614822,0.0000084384,0.0001719958],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0340622,"threshold_uncertainty_score":0.06772786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02701988538653783,"score_gpt":0.3135985775704836,"score_spread":0.2865786921839458,"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."}}