{"id":"W2946249536","doi":"10.31899/rh4.1234","title":"Population level impact of vouchers on access in Uganda","year":2012,"lang":"en","type":"report","venue":"","topic":"Poverty, Education, and Child Welfare","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Impact","funders":"","keywords":"Voucher; Population; Geography; Business; Computer science; Environmental health; World Wide Web; Medicine","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":[0.002437224,0.000249446,0.0005314775,0.001200091,0.0009294452,0.001497584,0.0006812236,0.0007541422,0.006575086],"category_scores_gemma":[0.008389763,0.000458785,0.0006476386,0.002151995,0.0006956407,0.001299842,0.003178786,0.001176328,0.0004969889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00338205,"about_ca_system_score_gemma":0.003595594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05511441,"about_ca_topic_score_gemma":0.1220527,"domain_scores_codex":[0.9966758,0.001460725,0.0001530198,0.000115789,0.0003630793,0.001231465],"domain_scores_gemma":[0.9947961,0.001788621,0.001287017,0.0002061534,0.0008764007,0.001045719],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001917067,0.0007879242,0.8923841,0.000712528,0.0003845461,0.002465608,0.006223905,0.006282856,0.0007342786,0.01034024,0.01665913,0.06110787],"study_design_scores_gemma":[0.00007025305,0.0005276864,0.9840752,0.0002140203,0.0001526747,0.0004523556,0.004691523,0.001087301,0.0002984108,0.001015413,0.007380707,0.00003454606],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9840762,0.0008262958,0.00009331672,0.00108291,0.00002607636,0.00008545448,0.003229994,0.00001800564,0.0105618],"genre_scores_gemma":[0.9952782,0.0005669745,0.0001657902,0.000155999,0.00001142657,0.00009285995,0.0007113784,0.000005039254,0.003012365],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05511441,"threshold_uncertainty_score":0.1095873,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1600507744337932,"score_gpt":0.438169937367548,"score_spread":0.2781191629337548,"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."}}