{"id":"W2147243077","doi":"10.1016/j.jinteco.2015.01.008","title":"High-end variety exporters defying gravity: Micro facts and aggregate implications","year":2015,"lang":"en","type":"article","venue":"Journal of International Economics","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Destinations; Diversification (marketing strategy); Variety (cybernetics); Aggregate (composite); Economics; Economic geography; Aggregate data; Gravity model of trade; International economics; International trade; Business; Geography; Marketing; Computer science; Tourism; Mathematics","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":[0.00096125,0.0001621189,0.0005410616,0.001023281,0.0008605481,0.002587856,0.0004148305,0.000819431,0.01018174],"category_scores_gemma":[0.006458203,0.0001038433,0.0002601731,0.001625823,0.00142153,0.001636666,0.001137593,0.001022627,0.0009357245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003436858,"about_ca_system_score_gemma":0.0002287172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0040135,"about_ca_topic_score_gemma":0.003923031,"domain_scores_codex":[0.9995328,0.00007842489,0.00002704296,0.0001250476,0.00009961325,0.0001371244],"domain_scores_gemma":[0.9919077,0.002856042,0.002586914,0.001046754,0.0008624267,0.0007400212],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004381745,0.0001876545,0.9445117,0.00004390853,0.0001422093,0.001044403,0.001927515,0.001010285,0.001394963,0.02111045,0.008663756,0.01952505],"study_design_scores_gemma":[0.00005514084,0.0001097,0.9642946,0.00002572068,0.0001626861,0.0004292422,0.006888824,0.002504603,0.0007902536,0.02035014,0.00436484,0.00002421522],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908091,0.0001565681,0.0002856409,0.001608333,0.0000182256,0.000004771719,0.0003317093,0.00002957951,0.006756131],"genre_scores_gemma":[0.999153,0.00004069761,0.0000501852,0.00009956989,0.00005051845,9.361561e-7,0.0001347084,0.000004245761,0.0004661625],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01018174,"threshold_uncertainty_score":0.03406125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07443465498612611,"score_gpt":0.2345081402349678,"score_spread":0.1600734852488417,"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."}}