{"id":"W3030334635","doi":"10.1007/s40258-020-00591-8","title":"Using a Formal Strategy of Priority Setting to Mitigate Austerity Effects Through Gains in Value: The Role of Program Budgeting and Marginal Analysis (PBMA) in the Brazilian Public Healthcare System","year":2020,"lang":"en","type":"article","venue":"Applied Health Economics and Health Policy","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Vancouver Coastal Health Research Institute; University of British Columbia; Vancouver Coastal Health","funders":"","keywords":"Austerity; Public economics; Health economics; Health care; Economics; Disinvestment; Population health; Health policy; Context (archaeology); Public health; Population; Population ageing; Actuarial science; Economic growth; Medicine; Macroeconomics; Political science; Environmental health","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.01943883,0.0002949472,0.001946985,0.0005593607,0.0004799861,0.000109496,0.0003648399,0.0001624663,0.000001905367],"category_scores_gemma":[0.0002690824,0.0002954949,0.0001093072,0.001082711,0.0001313535,0.0003113089,0.0001662553,0.0004488543,0.000003965668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001035999,"about_ca_system_score_gemma":0.001641464,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06969017,"about_ca_topic_score_gemma":0.01169061,"domain_scores_codex":[0.9923184,0.0007888278,0.004948689,0.0007245384,0.00009710337,0.00112244],"domain_scores_gemma":[0.9949952,0.0006705392,0.003346079,0.0004511647,0.00004202465,0.0004949369],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00004919708,0.000101762,0.1068521,0.008433271,0.00008941557,3.617899e-7,0.03386569,0.0022234,0.000001346537,0.8379777,0.00003904794,0.01036669],"study_design_scores_gemma":[0.003077047,0.001054553,0.691128,0.0005324118,0.00003580646,0.00001490531,0.04373759,0.2356299,0.000005835107,0.01578854,0.008249344,0.0007461183],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7748612,0.002282925,0.0002986655,0.2180294,0.00004149257,0.003862726,0.0002521788,0.00002221402,0.00034917],"genre_scores_gemma":[0.9649885,0.0006418817,0.003426079,0.03044217,0.0002126717,0.000233213,0.00002594611,0.00002905386,5.107494e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8221892,"threshold_uncertainty_score":0.9999497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3350548916707679,"score_gpt":0.4823258284822257,"score_spread":0.1472709368114578,"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."}}