{"id":"W2599594298","doi":"10.1108/jeas-06-2016-0015","title":"Financial depth and the trade openness-economic growth nexus","year":2017,"lang":"en","type":"article","venue":"Journal of economic and administrative sciences.","topic":"Fiscal Policy and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University","funders":"Innovative Research Group Project of the National Natural Science Foundation of China","keywords":"Openness to experience; Economics; Foreign direct investment; Nexus (standard); Gross fixed capital formation; Capital formation; Macroeconomics; International economics; Monetary economics; Panel data; Financial sector development; Finance; Financial capital; Human capital; Econometrics; Economic growth; Financial sector","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":[0.0007664618,0.0001728107,0.00018864,0.001387309,0.0002610723,0.001502478,0.0001672142,0.0002571658,0.002928668],"category_scores_gemma":[0.003985347,0.00007215491,0.000170189,0.002086726,0.0008566444,0.001120672,0.0008931456,0.00070177,0.0001950566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000484883,"about_ca_system_score_gemma":0.0004153399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001735163,"about_ca_topic_score_gemma":0.001856605,"domain_scores_codex":[0.9997789,0.00006982969,0.00002036174,0.00003554663,0.00005148953,0.00004384926],"domain_scores_gemma":[0.9912327,0.003854818,0.003902412,0.0002327761,0.0003130938,0.0004641579],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002351119,0.00007643527,0.9399388,0.0001843208,0.0001233981,0.0004081011,0.0004754897,0.003464474,0.0005582993,0.02302223,0.001433821,0.03007954],"study_design_scores_gemma":[0.00001450071,0.0000880833,0.9618845,0.0002486038,0.00009406333,0.0003128777,0.00151559,0.004274367,0.0007045102,0.02324303,0.007597084,0.00002283493],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9738393,0.004000361,0.001177164,0.002310012,0.00005516025,0.00001559657,0.0007384657,0.00001320109,0.01785076],"genre_scores_gemma":[0.9983521,0.0007261461,0.0002049564,0.00009307499,0.00004136994,0.000003309521,0.0001909427,0.000001707727,0.0003862608],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002928668,"threshold_uncertainty_score":0.009797394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08934656284511328,"score_gpt":0.303819358807729,"score_spread":0.2144727959626157,"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."}}