{"id":"W2946467135","doi":"10.1002/pam.22199","title":"Does Medicare Coverage Improve Cancer Detection and Mortality Outcomes?","year":2020,"lang":"en","type":"article","venue":"Journal of Policy Analysis and Management","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging; School of Pharmacy, University of Southern California; Leonard D. Schaeffer Center for Health Policy and Economics; National Cancer Institute; National Institutes of Health; University of Southern California; Wisconsin Alumni Research Foundation","keywords":"Medicine; Population; Health care; Cancer; Demography; Breast cancer; Lung cancer; Gerontology; Medicaid; Logistic regression; Environmental health; Oncology; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005769104,0.0002515511,0.0006371514,0.001202145,0.0003684725,0.001270953,0.0007187723,0.001851023,0.004815135],"category_scores_gemma":[0.04388547,0.000169049,0.0014149,0.001629624,0.0007408875,0.001655159,0.001346666,0.0009678399,0.000321899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001508104,"about_ca_system_score_gemma":0.001761982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01866716,"about_ca_topic_score_gemma":0.01870502,"domain_scores_codex":[0.9947351,0.002912529,0.0002239687,0.0004101601,0.0006798188,0.001038342],"domain_scores_gemma":[0.9783049,0.01066758,0.007474569,0.000883858,0.0008602413,0.001808865],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009528702,0.0004875425,0.9324386,0.0002199113,0.0009855423,0.0001401316,0.0002295548,0.001278194,0.0001608668,0.002052011,0.003622464,0.05743236],"study_design_scores_gemma":[0.00008026939,0.0004336042,0.9927521,0.000119944,0.0003972113,0.000093963,0.0001737684,0.0007057364,0.0001498049,0.00131787,0.003766035,0.000009911923],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9171206,0.01923875,0.0007804119,0.04708342,0.0003256514,0.00007511971,0.002982058,0.00006486009,0.01232905],"genre_scores_gemma":[0.9953557,0.00130164,0.0001850758,0.002148858,0.0002392381,0.00000964998,0.0003531247,0.000005287894,0.0004013782],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01866716,"threshold_uncertainty_score":0.037117,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03223883169150197,"score_gpt":0.3088566221617939,"score_spread":0.2766177904702919,"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."}}