{"id":"W2972979332","doi":"10.1093/jnci/djz184","title":"Long-Term Outcomes and Cost-Effectiveness of Breast Cancer Screening With Digital Breast Tomosynthesis in the United States","year":2019,"lang":"en","type":"article","venue":"JNCI Journal of the National Cancer Institute","topic":"Digital Radiography and Breast Imaging","field":"Medicine","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Center for Advancing Translational Sciences; Audrey and Theodor Geisel School of Medicine at Dartmouth; Georgetown University; University of California, San Francisco; National Cancer Institute; Kaiser Permanente; University of Toronto; Kaiser Permanente Washington Health Research Institute; Norris Cotton Cancer Center; Breast Cancer Society of Canada; Dartmouth College; Hologic; University of Wisconsin-Madison","keywords":"Medicine; Breast cancer; Breast cancer screening; Mammography; Cohort; Cost effectiveness; Digital mammography; Cancer; Oncology; Demography; Internal medicine; Gynecology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003418093,0.0006708525,0.0006123281,0.0006724954,0.0001873317,0.001322338,0.000631257,0.0007212806,0.002378997],"category_scores_gemma":[0.009528856,0.0003006161,0.002094883,0.0006684564,0.0004070241,0.0008384591,0.0006647852,0.000665557,0.0001177293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004809499,"about_ca_system_score_gemma":0.002023842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03045539,"about_ca_topic_score_gemma":0.02114435,"domain_scores_codex":[0.9988495,0.0007696286,0.00005528915,0.0001082732,0.00009948365,0.0001179428],"domain_scores_gemma":[0.9975175,0.0016442,0.0003808485,0.00007014049,0.000228221,0.0001590886],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.004990425,0.0006341725,0.164867,0.0005654483,0.002739309,0.0003680908,0.00007515509,0.7919663,0.0005083451,0.002624962,0.00283569,0.02782506],"study_design_scores_gemma":[0.001982384,0.0055558,0.2169317,0.001151713,0.007894931,0.0009707542,0.0005721199,0.7469046,0.001983445,0.01119692,0.004679673,0.0001759119],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9871231,0.003562445,0.001747724,0.001241031,0.00003986276,0.0001081332,0.00296487,0.00002984461,0.003182899],"genre_scores_gemma":[0.9976577,0.0005580956,0.0005004496,0.0001538566,0.000005691861,0.00004847138,0.0008798979,0.00000276561,0.0001931602],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03045539,"threshold_uncertainty_score":0.06055623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03319979960732257,"score_gpt":0.3215147978729913,"score_spread":0.2883149982656688,"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."}}