{"id":"W3088587985","doi":"10.5430/ijba.v11n5p81","title":"USA, EU and China as the Leading Actor in the World Trade and Cybersecurity, Divergences and Convergences","year":2020,"lang":"en","type":"article","venue":"International Journal of Business Administration","topic":"European Union Policy and Governance","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Protectionism; Multilateralism; China; International trade; Context (archaeology); Dilemma; European union; Convergence (economics); Normative; Political science; Deep integration; Economics; International economics; Business; Law; Economic growth; Politics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004781816,0.00005883486,0.00007732436,0.00003972023,0.0001612921,0.0002296973,0.0002527431,0.00001933908,0.00005382754],"category_scores_gemma":[0.000379288,0.00003677479,0.00001684166,0.0001774167,0.0002643952,0.0004879388,0.00002728816,0.0001265106,0.000001741684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000110447,"about_ca_system_score_gemma":0.00009460063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003859517,"about_ca_topic_score_gemma":0.003181791,"domain_scores_codex":[0.9991142,0.0001399552,0.0002075373,0.00008106223,0.0003862818,0.00007100723],"domain_scores_gemma":[0.9994504,0.0001732743,0.0002362111,0.00002418685,0.00006694617,0.0000490243],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0003770152,0.0001284867,0.1938172,0.0000321831,0.0001013021,0.0002378962,0.1250435,0.0000347452,0.0009626145,0.6592649,0.003126693,0.01687342],"study_design_scores_gemma":[0.0002728089,0.00007150599,0.9418512,0.000059047,0.00001382236,0.00006991735,0.003886882,0.0000630501,0.0001345719,0.002150547,0.05134724,0.00007942866],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8719949,0.0002752702,0.00003421815,0.1217629,0.0003161594,0.00005959026,0.000005506368,0.000002180926,0.005549357],"genre_scores_gemma":[0.9961628,0.001508923,0.00002558773,0.001726189,0.0004607596,6.638534e-7,5.75861e-7,0.000002169329,0.0001122796],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7480339,"threshold_uncertainty_score":0.2214977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04078636252783005,"score_gpt":0.334956959472945,"score_spread":0.2941705969451149,"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."}}