{"id":"W2924731061","doi":"10.1017/s1474745618000459","title":"Trade Commitments and Data Flows: The National Security Wildcard","year":2019,"lang":"en","type":"article","venue":"World Trade Review","topic":"World Trade Organization Law","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"International trade; National security; European union; Focus (optics); Political science; Business; Law","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":[0.01313698,0.0002920333,0.0004847137,0.004106964,0.002545134,0.0161503,0.001125311,0.0050285,0.0165442],"category_scores_gemma":[0.04585256,0.0003710558,0.0003777812,0.006936066,0.008259512,0.01285549,0.004106626,0.005390038,0.0007562605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00565315,"about_ca_system_score_gemma":0.006158535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008330475,"about_ca_topic_score_gemma":0.008772128,"domain_scores_codex":[0.9882449,0.006008653,0.0005658494,0.0008925472,0.003631138,0.000656862],"domain_scores_gemma":[0.9545975,0.03546901,0.003117428,0.002107023,0.003962313,0.0007466089],"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":[0.000007618293,0.000004625367,0.0003084116,0.00002530344,0.000003282082,0.00002343869,0.00008688313,0.0004215815,0.00001978873,0.9874526,0.004443035,0.00720359],"study_design_scores_gemma":[0.00001449942,0.00002397756,0.001747278,0.001087691,0.00001868979,0.00009107094,0.001118156,0.003009107,0.0002073808,0.8537052,0.1389393,0.00003744365],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03187844,0.01475666,0.02272347,0.1859478,0.001632518,0.0001076677,0.0008352697,0.0001083746,0.7420098],"genre_scores_gemma":[0.9380602,0.01075034,0.006724971,0.01491782,0.001373724,0.0001717796,0.0002502233,0.00009271437,0.02765809],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0165442,"threshold_uncertainty_score":0.06947583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05944689069359935,"score_gpt":0.3562055709195979,"score_spread":0.2967586802259986,"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."}}