{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002347011,0.0001888137,0.0001935798,0.001674191,0.002850675,0.005456182,0.0003201035,0.00104526,0.00449313],"category_scores_gemma":[0.001616804,0.00008643104,0.0001858251,0.002580679,0.003910741,0.003663131,0.00289134,0.001070934,0.0001734661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003864894,"about_ca_system_score_gemma":0.005385293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01500107,"about_ca_topic_score_gemma":0.02124394,"domain_scores_codex":[0.9988689,0.0004940212,0.00003900897,0.0001146697,0.0002147973,0.0002685693],"domain_scores_gemma":[0.9992526,0.0002603109,0.0001171956,0.0000549227,0.0001616459,0.0001532992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005365549,0.00004106978,0.03456858,0.0001252071,0.00002444529,0.00084202,0.01409184,0.0006257917,0.0003904836,0.8930417,0.005339338,0.05085586],"study_design_scores_gemma":[0.00003794286,0.0001638368,0.1192695,0.001695459,0.000136681,0.001026329,0.1244935,0.004228458,0.001953579,0.218409,0.528505,0.00008072728],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6099488,0.008383624,0.00189181,0.02090615,0.0002453449,0.000042487,0.00008653598,0.00002170415,0.3584737],"genre_scores_gemma":[0.9863008,0.002399215,0.000458854,0.001097987,0.00002279023,0.00001628389,0.00003236307,0.00000760562,0.009664009],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01500107,"threshold_uncertainty_score":0.02982748,"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."}}