{"id":"W2518975948","doi":"10.1186/s12889-016-3403-4","title":"Countdown to 2015 country case studies: what can analysis of national health financing contribute to understanding MDG 4 and 5 progress?","year":2016,"lang":"en","type":"article","venue":"BMC Public Health","topic":"Global Maternal and Child Health","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Global Health Research; Public Health Ontario; University of Toronto; SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"Countdown; Millennium Development Goals; Medicine; Tanzania; Economic growth; Per capita; Public health; Health policy; Developing country; Environmental health; Socioeconomics; Health care; Population; Economics","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":[0.04221302,0.0008043576,0.0008884197,0.004796794,0.001644764,0.00528969,0.002095848,0.001919083,0.007185245],"category_scores_gemma":[0.09282284,0.0004985209,0.002016681,0.008207371,0.002061772,0.006775753,0.004878056,0.001749082,0.0004226789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01389642,"about_ca_system_score_gemma":0.008169333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02537387,"about_ca_topic_score_gemma":0.02290259,"domain_scores_codex":[0.9665935,0.02671992,0.001566419,0.0008590265,0.002421927,0.001839223],"domain_scores_gemma":[0.9178419,0.05386449,0.01282191,0.004245953,0.009251886,0.00197387],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001143948,0.001059869,0.3659178,0.007209627,0.001473784,0.004721862,0.02801476,0.02332556,0.000617027,0.2632623,0.1083745,0.1948789],"study_design_scores_gemma":[0.0004806317,0.001258041,0.2058842,0.0298374,0.001104594,0.002504613,0.1293996,0.03818819,0.003474238,0.128236,0.4591733,0.0004592864],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6927388,0.02684738,0.04519379,0.08399878,0.00129393,0.007235905,0.02054003,0.0001738876,0.1219775],"genre_scores_gemma":[0.9354208,0.007368414,0.03943049,0.004406286,0.0001797609,0.005683981,0.005207505,0.00004218757,0.00226069],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04221302,"threshold_uncertainty_score":0.2232465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09023919924364425,"score_gpt":0.3958333623680693,"score_spread":0.3055941631244251,"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."}}