{"id":"W2888498061","doi":"10.1177/0272989x18792284","title":"Economically Efficient Hepatitis C Virus Treatment Prioritization Improves Health Outcomes","year":2018,"lang":"en","type":"article","venue":"Medical Decision Making","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Institute on Aging; Ivey Business School, Western University; Natural Sciences and Engineering Research Council of Canada; U.S. Department of Veterans Affairs","keywords":"Medicine; Prioritization; Population; Quality-adjusted life year; Liver disease; Disease burden; Hepatitis C virus; Economic evaluation; Intensive care medicine; Cost effectiveness; Environmental health; Internal medicine; Immunology; Virus; Risk analysis (engineering); Business; Pathology","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":[0.004115105,0.000920371,0.000686295,0.0006939913,0.0003077692,0.001070231,0.0005563947,0.0007987223,0.002830876],"category_scores_gemma":[0.01177181,0.0003372334,0.0007155376,0.0006323854,0.0004122246,0.0008221376,0.0008589648,0.0009499947,0.0001499539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00355308,"about_ca_system_score_gemma":0.003943516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007782002,"about_ca_topic_score_gemma":0.004603068,"domain_scores_codex":[0.9979392,0.001380433,0.0000437233,0.0001290493,0.0001992161,0.0003083178],"domain_scores_gemma":[0.995488,0.002946606,0.0009513095,0.0001465292,0.0002308316,0.0002367371],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007324435,0.0004278033,0.01170362,0.0001353417,0.0002274861,0.00005211165,0.00004774897,0.9562012,0.0008915311,0.005013072,0.001161873,0.02340577],"study_design_scores_gemma":[0.0005612982,0.00167375,0.0130972,0.000106051,0.0002798554,0.0001293212,0.0001593943,0.9603945,0.001112116,0.02018815,0.002255504,0.00004293212],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9165269,0.001410505,0.06858625,0.002541851,0.00007034268,0.0004321776,0.0005628834,0.0001283627,0.00974066],"genre_scores_gemma":[0.9922558,0.0002511591,0.006659059,0.0001727439,0.00001462553,0.00007026215,0.0001055624,0.00001033435,0.0004604059],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007782002,"threshold_uncertainty_score":0.02577949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2060949708128538,"score_gpt":0.4688944917542109,"score_spread":0.2627995209413571,"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."}}