{"id":"W4388445264","doi":"10.1515/jgd-2023-0013","title":"Trade Boomers: Evidence from the Commodities-for-Manufactures Boom in Brazil","year":2023,"lang":"en","type":"article","venue":"Journal of Globalization and Development","topic":"Global Health Care Issues","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Economics; Baby boom; China; Free trade; Boom; International economics; Demographic economics; International trade; Population; Geography","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":[0.001100078,0.000236456,0.0002562922,0.001322404,0.0007277313,0.001083894,0.0004320391,0.0005614244,0.004812684],"category_scores_gemma":[0.00489946,0.0002203858,0.0005829314,0.002666362,0.001039949,0.0008182579,0.001491146,0.0009405737,0.0002468897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0011018,"about_ca_system_score_gemma":0.001326358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1499333,"about_ca_topic_score_gemma":0.1958415,"domain_scores_codex":[0.9995709,0.000104362,0.00002964259,0.00007214044,0.00007280213,0.0001501512],"domain_scores_gemma":[0.9955065,0.000971368,0.002412006,0.000224821,0.0004303239,0.0004549069],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001538675,0.00008718263,0.9756584,0.0002544153,0.0001508215,0.0005521412,0.003829638,0.0001889032,0.0003224199,0.003246588,0.003271373,0.01228429],"study_design_scores_gemma":[0.00001518195,0.00006443281,0.9839264,0.0002721876,0.0001207316,0.0001612094,0.007058355,0.00031926,0.0002320737,0.0005941535,0.007223294,0.00001281781],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9775996,0.003739449,0.0001531188,0.005843639,0.00003925038,0.00002492466,0.002948078,0.00000824949,0.009643759],"genre_scores_gemma":[0.9960545,0.002227216,0.00005186104,0.0003613239,0.00002434165,0.000008802777,0.0007357427,0.000005216299,0.000530997],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1499333,"threshold_uncertainty_score":0.2981213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1115175657939328,"score_gpt":0.4526084950254622,"score_spread":0.3410909292315294,"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."}}