{"id":"W4312127909","doi":"10.3390/jrfm15120596","title":"Global Spillovers of a Chinese Growth Slowdown","year":2022,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"China; Economics; Rest (music); Slowdown; Commodity; Shock (circulatory); Dynamic stochastic general equilibrium; Chinese economy; Monetary economics; International economics; Emerging markets; Monetary policy; International trade; Macroeconomics; Geography; Market economy; Economic growth","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":[0.0005209918,0.0003747686,0.0003287582,0.0008425862,0.000433819,0.001243009,0.0001703644,0.0003214841,0.002815586],"category_scores_gemma":[0.001115988,0.000165291,0.0004846911,0.0007085216,0.0005315241,0.0008278551,0.001267783,0.0006430586,0.0001641923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009677233,"about_ca_system_score_gemma":0.0005686252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01464382,"about_ca_topic_score_gemma":0.01056985,"domain_scores_codex":[0.9998786,0.00001981067,0.000006254571,0.00002970751,0.00002640903,0.00003916775],"domain_scores_gemma":[0.9995812,0.00007523518,0.0001574086,0.00004399526,0.00008798065,0.0000542603],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008044107,0.0001896439,0.6091281,0.0005085391,0.0008990656,0.01014715,0.004089511,0.09791657,0.02221404,0.1328799,0.009582339,0.1116407],"study_design_scores_gemma":[0.00006261429,0.0003212265,0.8822818,0.0001663516,0.0004929506,0.0007504287,0.003665312,0.06345302,0.005583256,0.02370918,0.01940744,0.0001064724],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9779017,0.00057309,0.001718556,0.001029121,0.00003949294,0.00001474483,0.0002642153,0.00007268685,0.01838633],"genre_scores_gemma":[0.99861,0.0003405598,0.0001302289,0.00006673672,0.00001832734,0.000002398103,0.00007453054,0.000005308159,0.0007518744],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01464382,"threshold_uncertainty_score":0.02911717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005321247136767091,"score_gpt":0.1904685413064604,"score_spread":0.1851472941696933,"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."}}