{"id":"W4255947004","doi":"10.1111/1468-0319.12418","title":"The global impact of a sharper US‐China slowdown","year":2019,"lang":"en","type":"article","venue":"Economic Outlook","topic":"Regional resilience and development","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economics; China; International economics; Us dollar; Slowdown; Recession; Volatility (finance); Financial crisis; Emerging markets; Liberian dollar; Renminbi; Monetary economics; Exchange rate; Macroeconomics; Geography","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":[0.001021521,0.0006877718,0.0003496555,0.000639108,0.0007353969,0.002114309,0.0004485458,0.001118751,0.01114713],"category_scores_gemma":[0.002291628,0.0002003572,0.0008006854,0.0006970449,0.000486641,0.002267784,0.001208319,0.001129122,0.0008491093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001748623,"about_ca_system_score_gemma":0.001913272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0761231,"about_ca_topic_score_gemma":0.0495447,"domain_scores_codex":[0.9998024,0.00004304642,0.000008905702,0.00002811757,0.00002917306,0.00008827633],"domain_scores_gemma":[0.9994301,0.00007042995,0.00008037188,0.00003761031,0.0002049362,0.0001765262],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001251697,0.0002606376,0.2547295,0.000859438,0.0007188577,0.003509575,0.0009775286,0.3441942,0.00550358,0.124633,0.1889838,0.07437821],"study_design_scores_gemma":[0.0004897179,0.000768174,0.309154,0.0006711995,0.0007398554,0.0007475193,0.005124386,0.3925742,0.005335202,0.08280696,0.2012688,0.000320072],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8424597,0.002908778,0.006144451,0.04571883,0.001952713,0.00009294502,0.009576724,0.001072448,0.09007333],"genre_scores_gemma":[0.990729,0.001027425,0.0006824362,0.001165075,0.00006083828,0.00002607845,0.001623131,0.00006877319,0.004617456],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0761231,"threshold_uncertainty_score":0.1513601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01005757775742719,"score_gpt":0.2350153442613616,"score_spread":0.2249577665039344,"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."}}