{"id":"W6958358400","doi":"10.6084/m9.figshare.12744349","title":"Additional file 1 of Geographic Targeting and Normative Frames: Revisiting the Equity of Conditional Cash Transfer Program Distribution in Bolivia, Colombia, Ecuador, and Peru","year":2020,"lang":"en","type":"article","venue":"Figshare","topic":"Poverty, Education, and Child Welfare","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Equity (law); Conditional cash transfer; Cash; Distribution (mathematics); Normative; Payment","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002512034,0.0004953725,0.0005082955,0.002851923,0.0009126933,0.001289645,0.001781253,0.000548378,0.7160098],"category_scores_gemma":[0.0412066,0.0003883522,0.0003780411,0.007492997,0.0002583993,0.001961952,0.001138676,0.0009834657,0.05254679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002122994,"about_ca_system_score_gemma":0.002596247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07629211,"about_ca_topic_score_gemma":0.07976796,"domain_scores_codex":[0.9989324,0.0003744994,0.0001292141,0.0001635597,0.0002405959,0.0001598135],"domain_scores_gemma":[0.9676151,0.02372418,0.001983495,0.001365395,0.004870766,0.0004409619],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001037694,0.00005351709,0.006501794,0.0005982509,0.00001573805,0.00003157292,0.0004482002,0.000360595,0.00001791865,0.003699135,0.9805554,0.00761405],"study_design_scores_gemma":[0.001418752,0.0001129893,0.138523,0.002313523,0.0001374718,0.0001834333,0.006554278,0.002094107,0.0004241774,0.01144616,0.8366948,0.00009733135],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.001078342,0.00001748724,0.0002802814,0.0001907154,0.00001467977,0.0001414521,0.992581,0.00006796575,0.005628115],"genre_scores_gemma":[0.05704558,0.0001921475,0.005476509,0.0003749377,0.00007322142,0.004587734,0.9062965,0.0005670708,0.02538638],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7160098,"threshold_uncertainty_score":0.4050775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02278988290702408,"score_gpt":0.2816054405022559,"score_spread":0.2588155575952318,"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."}}