{"id":"W4413680347","doi":"10.22215/cjers.v18i1.4952","title":"The Digital Silk Road in Europe: China’s Soft Power Maneuvers at Euro 2024","year":2025,"lang":"en","type":"article","venue":"The Canadian Journal of European and Russian Studies","topic":"Economic Issues in Ukraine","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Soft power; China; SILK; Environmental science; Engineering; Geography; Telecommunications; Archaeology","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":[0.001644044,0.0001694948,0.0001867701,0.0007890483,0.00359881,0.002670556,0.0003508526,0.000781069,0.002669289],"category_scores_gemma":[0.001449197,0.0001219942,0.0001333113,0.00117551,0.003177579,0.001953317,0.001942674,0.0008497642,0.0001062408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00411938,"about_ca_system_score_gemma":0.002319932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02748148,"about_ca_topic_score_gemma":0.04347233,"domain_scores_codex":[0.999386,0.0002724902,0.00002063236,0.00005595406,0.00008569944,0.0001793078],"domain_scores_gemma":[0.9994029,0.0002323579,0.0001045403,0.000031396,0.00006002478,0.0001688517],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001399951,0.00010482,0.1008061,0.0001808116,0.00002603889,0.003080583,0.7837679,0.0005877939,0.002924082,0.07530771,0.005711681,0.02736263],"study_design_scores_gemma":[0.00001102813,0.00009592531,0.1395565,0.0001421207,0.0000126508,0.0002235109,0.7723107,0.0007121182,0.0009693843,0.002160574,0.08376697,0.00003853586],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9885786,0.0001918964,0.0001338558,0.001023756,0.00001510043,0.000008694103,0.00002710343,0.000003684672,0.01001744],"genre_scores_gemma":[0.9969949,0.0001330863,0.00005764882,0.0001621851,0.000003889189,0.000005962222,0.00001383572,0.00000310975,0.002625361],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02748148,"threshold_uncertainty_score":0.05464303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01983020598765952,"score_gpt":0.2191854497029528,"score_spread":0.1993552437152933,"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."}}