{"id":"W4403674516","doi":"10.2139/ssrn.4991804","title":"Does Earmarking Lead to More Per Capita Public Health Spending?","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Global Health Care Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan; University of Calgary","funders":"","keywords":"Per capita; Public spending; Lead (geology); Economics; Health spending; Public health; Public economics; Environmental health; Economic growth; Health care; Political science; Medicine; Health insurance; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001573261,0.0001708353,0.0002815897,0.0007748082,0.0004473265,0.003027051,0.0005200196,0.001923611,0.03060707],"category_scores_gemma":[0.01621854,0.0001332359,0.0007018246,0.001644153,0.0008680654,0.002231972,0.0006636704,0.00152296,0.002178353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001184603,"about_ca_system_score_gemma":0.002333618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01239536,"about_ca_topic_score_gemma":0.01424708,"domain_scores_codex":[0.9986088,0.0004038926,0.00007977326,0.0001418345,0.0002249946,0.0005407274],"domain_scores_gemma":[0.9849183,0.004269451,0.00702991,0.0003788954,0.001373144,0.002030343],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001852072,0.001381936,0.7998024,0.0003318397,0.0003387903,0.0005309487,0.0005342019,0.0006728799,0.0007605251,0.01433725,0.0415718,0.1378854],"study_design_scores_gemma":[0.0002185643,0.0006817656,0.9339447,0.0004111055,0.0004509643,0.000462145,0.004084513,0.00101119,0.001513344,0.01313116,0.04403969,0.00005087259],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8130987,0.00523227,0.0004167283,0.1186844,0.001786238,0.00002971785,0.004286138,0.0001001639,0.05636576],"genre_scores_gemma":[0.9841067,0.001797892,0.0002071599,0.006678863,0.0008605598,0.000009065369,0.0007119937,0.0000294716,0.005598328],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03060707,"threshold_uncertainty_score":0.1023909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04979183980425966,"score_gpt":0.4414247509206207,"score_spread":0.391632911116361,"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."}}