{"id":"W3106928301","doi":"10.2760/778748","title":"EU Trade in Value Added","year":2020,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Regional Development and Policy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"European union; International trade; Member state; Added value; Value (mathematics); Business; Commission; Global value chain; China; Member states; International economics; Economics; Geography; Finance; Comparative advantage","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":[0.001465366,0.0007494921,0.000624531,0.00453616,0.0005294848,0.005311973,0.0006179317,0.001234908,0.01301167],"category_scores_gemma":[0.004412555,0.000259315,0.0008306211,0.01405543,0.0005827356,0.001906079,0.002936932,0.001623242,0.005232194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002709651,"about_ca_system_score_gemma":0.001925776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009184785,"about_ca_topic_score_gemma":0.003058251,"domain_scores_codex":[0.9977921,0.0002638272,0.0001835924,0.0004810752,0.001014123,0.000265305],"domain_scores_gemma":[0.999083,0.000210486,0.0002112724,0.000127268,0.0003029077,0.00006499748],"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":[0.0003351269,0.0001098638,0.01561205,0.002741744,0.0003439481,0.0005398165,0.00111748,0.005335905,0.001489099,0.4151613,0.2152927,0.341921],"study_design_scores_gemma":[0.00001961973,0.00004608068,0.02202996,0.001266177,0.00004288278,0.0002061208,0.0004439035,0.0005667018,0.001005698,0.01573707,0.9586077,0.00002801763],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.07101864,0.04525184,0.004261499,0.007321463,0.002189628,0.00009133563,0.0853124,0.0005504851,0.7840027],"genre_scores_gemma":[0.6045898,0.05434888,0.01120151,0.004382401,0.0007688691,0.0004317173,0.1700756,0.0007951006,0.1534062],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01301167,"threshold_uncertainty_score":0.04352838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09526335737665882,"score_gpt":0.3925857613273116,"score_spread":0.2973224039506528,"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."}}