{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.01058432,0.0002750746,0.001230613,0.0003777794,0.0004336881,0.0001423442,0.0003886575,0.0002272837,0.002656631],"category_scores_gemma":[0.008497135,0.0002820302,0.0001960539,0.0002071621,0.0001647118,0.0001998741,0.0001177747,0.0001554593,0.004728923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001604078,"about_ca_system_score_gemma":0.0004556553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001799254,"about_ca_topic_score_gemma":0.002110197,"domain_scores_codex":[0.9934131,0.0002735134,0.004577077,0.0008272784,0.0003023987,0.0006066498],"domain_scores_gemma":[0.9950912,0.001991909,0.001707522,0.0006337435,0.0000847574,0.0004908793],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001389847,0.001206471,0.3314299,0.0002617728,0.0002975002,0.00001779637,0.005209679,0.0003805261,0.00001027733,0.1676377,0.04862257,0.4447868],"study_design_scores_gemma":[0.003894072,0.00159185,0.5720925,0.0008084899,0.00001452989,0.00002829839,0.0002780832,0.1901496,0.00002037546,0.04294324,0.1870929,0.00108611],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7463798,0.001296553,0.2097597,0.0352975,0.003202246,0.001100316,0.000197415,0.0001754757,0.002590948],"genre_scores_gemma":[0.9507164,0.0004904229,0.01814536,0.02916341,0.001017557,0.00009237026,0.00002966268,0.00005628535,0.0002885312],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4437007,"threshold_uncertainty_score":0.9999632,"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."}}