{"id":"W2994644621","doi":"","title":"Monetary News Shocks","year":2017,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Shock (circulatory); Monetary policy; Economics; Monetary economics; Inflation (cosmology); Forecast error; Residual; Variance (accounting); Econometrics; Interest rate; Contraction (grammar); Macroeconomics; Mathematics; Endocrinology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005707224,0.0003965259,0.0003679261,0.000968997,0.0003249302,0.002106114,0.0003293765,0.001049659,0.004528537],"category_scores_gemma":[0.006735381,0.000213806,0.0002626069,0.001076052,0.0002767098,0.001366576,0.0006092245,0.001319209,0.0006029397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00052565,"about_ca_system_score_gemma":0.0002622621,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002342616,"about_ca_topic_score_gemma":0.001990363,"domain_scores_codex":[0.9997649,0.00004374935,0.00001929538,0.00006517646,0.00007332174,0.000033603],"domain_scores_gemma":[0.9985176,0.0006382986,0.0005119871,0.00008602768,0.0001691913,0.00007695397],"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":[0.001379397,0.0005992183,0.2787629,0.0006704696,0.0004954773,0.001971618,0.001275535,0.09459456,0.009060676,0.3353676,0.04743459,0.228388],"study_design_scores_gemma":[0.000326778,0.000730233,0.3341159,0.000596129,0.0004800545,0.000983477,0.001770025,0.3229125,0.0145743,0.2320642,0.0911795,0.0002669776],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8877044,0.00336623,0.04095915,0.008166092,0.000989894,0.0001030884,0.006693794,0.0004052802,0.05161199],"genre_scores_gemma":[0.989509,0.001129395,0.00190223,0.0003876227,0.0004455438,0.00002995197,0.001558252,0.00003043697,0.005007557],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004528537,"threshold_uncertainty_score":0.01514953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1223724454219754,"score_gpt":0.3167120399553211,"score_spread":0.1943395945333457,"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."}}