{"id":"W3033139457","doi":"10.32559/et.2019.4.2","title":"Az agrárium versenyképessége az Európai Unióban: fókuszban a tejipar","year":2019,"lang":"hu","type":"article","venue":"Európai Tükör","topic":"Global Trade and Competitiveness","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"European union; Agricultural economics; Agricultural science; Revealed comparative advantage; Business; Production (economics); Consumption (sociology); Agriculture; Order (exchange); Added value; Dairy industry; Quarter (Canadian coin); International trade; Geography; Comparative advantage; Economics; Food science; Environmental science; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008204624,0.0006642469,0.0007677784,0.0009678468,0.0011422,0.005923452,0.0005715485,0.0009744731,0.0525412],"category_scores_gemma":[0.0008993697,0.0002366224,0.0003476594,0.001958682,0.0006198726,0.001975434,0.002028246,0.001373846,0.01827028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002064082,"about_ca_system_score_gemma":0.002254106,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01138453,"about_ca_topic_score_gemma":0.009646276,"domain_scores_codex":[0.9993483,0.00009523786,0.00003968458,0.0001387688,0.0002193727,0.0001586133],"domain_scores_gemma":[0.999738,0.00004243528,0.00005786204,0.00002987466,0.00007836555,0.0000533403],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001061932,0.0004653144,0.01473625,0.002727689,0.0002498771,0.00328894,0.002849716,0.002037799,0.01163263,0.09604684,0.1834205,0.6814824],"study_design_scores_gemma":[0.00001716645,0.00002230683,0.008036396,0.0003078722,0.00001914723,0.0004157316,0.0008356872,0.00015569,0.001366659,0.001953494,0.9868534,0.00001642215],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2012658,0.09249483,0.0127601,0.01435286,0.005197112,0.000154702,0.01950336,0.001438141,0.652833],"genre_scores_gemma":[0.4503698,0.06168157,0.02085951,0.00217041,0.0006515344,0.0001341749,0.01586295,0.001032752,0.4472372],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0525412,"threshold_uncertainty_score":0.1757678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01158928543452652,"score_gpt":0.193519939783305,"score_spread":0.1819306543487784,"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."}}