{"id":"W2315065932","doi":"10.19044/esj.2016.v12n7p396","title":"An Econometric Estimation Of Nigeria’s Export Competitiveness In The Global Market","year":2016,"lang":"en","type":"article","venue":"European Scientific Journal ESJ","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Exportation; Competition (biology); Order (exchange); Productivity; International trade; Estimation; Business; Revealed comparative advantage; Government (linguistics); Goods and services; Economics; Market share; International economics; Economy; Economic growth; Comparative advantage; Finance","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005438773,0.0001227981,0.0002609466,0.0003590867,0.0001518435,0.0003458592,0.0007785209,0.00002887267,0.0009242903],"category_scores_gemma":[0.000163753,0.00009039312,0.0001129453,0.0006187752,0.0001687407,0.0007236387,0.00004386612,0.0001001556,0.0005979142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001702271,"about_ca_system_score_gemma":0.00003592916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001082695,"about_ca_topic_score_gemma":0.0000150003,"domain_scores_codex":[0.9982639,0.0001463189,0.0008913523,0.0003383688,0.00006474375,0.0002953475],"domain_scores_gemma":[0.9988068,0.00005822547,0.0005675881,0.0004185103,0.00003980279,0.0001090994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007636812,0.0005572867,0.9152173,0.00002746783,0.00005550846,0.00009566981,0.002845713,0.001633499,0.00006734774,0.04900904,0.00376562,0.02664915],"study_design_scores_gemma":[0.001323876,0.0001644503,0.9253296,0.00007475892,0.000005709136,0.0002000336,0.001964771,0.001478683,0.00005071983,0.02497449,0.04407546,0.0003574441],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8978587,0.0002439868,0.003358115,0.0003396255,0.001235086,0.00009030771,0.0001690737,0.000008557396,0.09669649],"genre_scores_gemma":[0.9988959,0.00006933403,0.0004214493,0.00008830235,0.00009975637,0.000001213114,0.000005814892,0.00001132229,0.0004068975],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1010371,"threshold_uncertainty_score":0.999989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05239518406622679,"score_gpt":0.2344390908877194,"score_spread":0.1820439068214926,"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."}}