{"id":"W2460288775","doi":"10.24149/gwp276","title":"Is the Renminbi a Safe Haven?","year":2016,"lang":"en","type":"article","venue":"Federal Reserve Bank of Dallas, Globalization and Monetary Policy Institute Working Papers","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Tokyo Center for Economic Research","keywords":"Renminbi; Safe haven; Haven; Currency; Economics; Value (mathematics); Sample (material); Monetary economics; International economics; Exchange rate; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004712029,0.0002044518,0.0003390248,0.000147238,0.0002973023,0.00009590859,0.0003113035,0.0001268348,0.000219243],"category_scores_gemma":[0.0003435238,0.0001500315,0.0001370956,0.0003460838,0.0002517365,0.0001865215,0.0001395275,0.00008324857,0.00001331797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001078835,"about_ca_system_score_gemma":0.00005562006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00357125,"about_ca_topic_score_gemma":0.001988531,"domain_scores_codex":[0.9984774,0.00004165,0.0006373098,0.0004164914,0.00009926422,0.0003278749],"domain_scores_gemma":[0.9989697,0.00006440603,0.0003573846,0.0004572077,0.00003574747,0.0001155099],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001236564,0.00005312475,0.5620918,0.00005673275,0.0001528988,0.000002709102,0.0003460505,0.00008596391,0.00006740022,0.4211246,0.00357044,0.01232463],"study_design_scores_gemma":[0.001159743,0.00007389481,0.2150194,0.0001719336,0.00001372448,0.000006604419,0.00003543079,0.007440739,0.00002095624,0.02907116,0.7466144,0.0003719437],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4690089,0.003569151,0.002699896,0.04624856,0.001001021,0.0008427143,0.0006885673,0.00009622436,0.4758449],"genre_scores_gemma":[0.9923813,0.002046149,0.000261932,0.001606566,0.0001477926,0.000009452598,0.00003431182,0.00001525708,0.003497217],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.743044,"threshold_uncertainty_score":0.6118107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03658850759453375,"score_gpt":0.2539365768201155,"score_spread":0.2173480692255818,"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."}}