{"id":"W3126560979","doi":"10.21547/jss.719642","title":"The Relationship Between High-Tech Export and Economic Growth: A Panel Data Approach for Selected Countries","year":2021,"lang":"en","type":"article","venue":"Gaziantep University Journal of Social Sciences","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"China; Context (archaeology); Czech; Panel data; Agriculture; Business; High tech; Economy; International trade; Agricultural economics; Economics; Geography","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":[],"consensus_categories":[],"category_scores_codex":[0.00196024,0.00007495703,0.0002549142,0.0001028223,0.00125649,0.0001476954,0.0005429645,0.00006670326,0.00001169909],"category_scores_gemma":[0.00036818,0.00007434267,0.00005394215,0.0002389677,0.0004264434,0.000816685,0.0001242355,0.0001397521,0.000004559778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001032653,"about_ca_system_score_gemma":0.0002665684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009959667,"about_ca_topic_score_gemma":0.00007362691,"domain_scores_codex":[0.9991469,0.0000400976,0.0003066679,0.0002724939,0.0000372263,0.0001965471],"domain_scores_gemma":[0.9987455,0.0004574078,0.0005299793,0.0001198066,0.00009446814,0.00005281103],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002419324,0.00001247796,0.7137449,0.00001253726,0.00004902887,0.000001834682,0.0003608453,0.000002493854,0.00000186154,0.2836833,0.001926932,0.0001795645],"study_design_scores_gemma":[0.0006544939,0.0000732553,0.9247996,0.000005652602,0.00003521148,0.00002437835,0.001968603,0.0001677276,0.00002677887,0.03905912,0.03300552,0.0001797026],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9818158,0.0008419249,0.007977343,0.005573237,0.0002891054,0.0001066944,0.0004743967,0.0000081965,0.002913261],"genre_scores_gemma":[0.9971596,0.0002470351,0.001950357,0.00002412098,0.0002781787,1.786807e-7,0.00001663146,0.000003822271,0.0003200811],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2446242,"threshold_uncertainty_score":0.9664031,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1214531211939925,"score_gpt":0.2480373497571008,"score_spread":0.1265842285631083,"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."}}