{"id":"W2187353124","doi":"10.1111/caje.12216","title":"Public–private mix of health expenditure: A political economy and quantitative analysis","year":2016,"lang":"en","type":"article","venue":"Canadian Journal of Economics/Revue canadienne d économique","topic":"Global Health Care Issues","field":"Health Professions","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Public economics; Aggregate expenditure; Voting; Public health; Sample (material); Health care; Public expenditure; Economics; Democracy; Politics; Business; Economic growth; Political science; Public finance; Macroeconomics; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.003010409,0.0003946857,0.001053276,0.001316973,0.0007847516,0.002972054,0.0007327271,0.001345254,0.01471384],"category_scores_gemma":[0.005760877,0.000441654,0.0009728294,0.001689219,0.001788208,0.002372253,0.001338143,0.001212605,0.0005123614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003443164,"about_ca_system_score_gemma":0.001168236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004875811,"about_ca_topic_score_gemma":0.003341441,"domain_scores_codex":[0.9979955,0.001365208,0.00004205074,0.0001594688,0.000211275,0.0002265262],"domain_scores_gemma":[0.9946695,0.004251276,0.0004511283,0.0002481889,0.0001963508,0.0001834956],"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":[0.0001069384,0.0001935671,0.006634027,0.00009415437,0.0000752169,0.0001176318,0.0001522163,0.1809606,0.000513621,0.8035622,0.001835817,0.005753972],"study_design_scores_gemma":[0.0001151649,0.0001757769,0.007396537,0.00005655755,0.00004676732,0.0001129894,0.0004866498,0.623955,0.0003219015,0.3616206,0.005664138,0.00004803714],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5351374,0.001070933,0.3401591,0.009992118,0.00008712467,0.000529987,0.00298858,0.0001633351,0.1098713],"genre_scores_gemma":[0.9796684,0.0002665375,0.01127383,0.0001676211,0.00005828627,0.0002606088,0.0002849302,0.00001505979,0.008004762],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01471384,"threshold_uncertainty_score":0.04922277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3000884770685182,"score_gpt":0.3242727546239684,"score_spread":0.02418427755545022,"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."}}