{"id":"W4230473511","doi":"","title":"When Did Latin America fall behind?","year":2007,"lang":"en","type":"book-chapter","venue":"LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)","topic":"Economic Theory and Policy","field":"Economics, Econometrics and Finance","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Latin Americans; Inequality; Fell; Per capita; Economic inequality; Demographic economics; Development economics; Polarization (electrochemistry); Geography; Economics; Political science; Demography; Sociology; Cartography; Population","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001023495,0.0008920833,0.001372958,0.001140214,0.0005416246,0.0002716907,0.0009774355,0.001430674,0.001248821],"category_scores_gemma":[0.0002969233,0.001077885,0.0006779002,0.0001257095,0.0000675621,0.0004285594,0.000352787,0.001412154,0.001172668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00108858,"about_ca_system_score_gemma":0.0002938245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001021683,"about_ca_topic_score_gemma":0.0003227089,"domain_scores_codex":[0.99553,0.00006846449,0.001893961,0.001362642,0.0001585601,0.0009863924],"domain_scores_gemma":[0.9961078,0.0002662187,0.001670896,0.001154396,0.000164592,0.0006360947],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000984761,0.0001327937,0.0001436573,0.00008438416,0.0003102455,0.0001073738,0.001331565,0.00002089086,0.00001290664,0.9914838,0.004259975,0.002013925],"study_design_scores_gemma":[0.0006589148,0.00007060594,0.0003367933,0.000120792,0.00004764674,0.0002207195,0.0000367813,0.00007173649,0.00002412397,0.1311761,0.866266,0.0009698799],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0007840181,0.001634242,0.001763812,0.005891615,0.001317283,0.0004967194,0.0007429761,0.0003028565,0.9870665],"genre_scores_gemma":[0.658636,0.001247043,0.005039205,0.002227108,0.003913506,0.0001560147,0.001082771,0.0004066351,0.3272917],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8620059,"threshold_uncertainty_score":0.9998657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03988841114633554,"score_gpt":0.2366324036099291,"score_spread":0.1967439924635936,"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."}}