{"id":"W4236427250","doi":"10.25205/2542-0429-2021-21-4-24-46","title":"The Estimation of Various Shocks Influence on the Dynamics of Russian Macroeconomic Indicators in 2014–2018","year":2021,"lang":"en","type":"article","venue":"WORLD OF ECONOMICS AND MANAGEMENT","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economics; Dynamic stochastic general equilibrium; Shock (circulatory); Inflation (cosmology); Quarter (Canadian coin); Estimation; Oil price; Monetary economics; Russian economy; Econometrics; Macroeconomics; Monetary policy; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009404368,0.0001209221,0.0003419361,0.0003244169,0.00006858849,0.0000351301,0.000268465,0.00003986866,0.000059419],"category_scores_gemma":[0.00002730855,0.0001068008,0.00008047197,0.0002170807,0.000158919,0.00007139856,0.0001816948,0.00007949594,0.000003753349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001139285,"about_ca_system_score_gemma":0.0000211353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002367321,"about_ca_topic_score_gemma":0.002804958,"domain_scores_codex":[0.9986255,0.00002139279,0.0008965028,0.0002745642,0.00001850445,0.0001635277],"domain_scores_gemma":[0.9985777,0.0001699806,0.0006960392,0.000514731,0.0000107562,0.00003080531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002490089,0.00005911596,0.0558119,0.00007165752,0.00007275571,5.009801e-7,0.0000690141,0.004565061,2.840063e-7,0.9331287,0.00005270817,0.006143383],"study_design_scores_gemma":[0.000551742,0.00005206684,0.2991204,0.00005730821,0.00001633742,6.109473e-7,0.0001549287,0.499783,0.00004704679,0.1915949,0.008425133,0.0001965382],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9492806,0.0003697012,0.0002319875,0.001715816,0.0001572087,0.0002951801,0.0001137553,0.000002751401,0.04783307],"genre_scores_gemma":[0.9952461,0.003561405,0.0003612837,0.00009788532,0.000006711276,0.000018412,0.00001178949,0.00001074187,0.0006856762],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7415339,"threshold_uncertainty_score":0.4355211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007926858203905684,"score_gpt":0.1979217096522453,"score_spread":0.1899948514483396,"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."}}