{"id":"W4319232201","doi":"10.2139/ssrn.4347645","title":"Information Acquisition Ahead of Monetary Policy Announcements","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Italy: Economic History and Contemporary Issues","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Bank of Canada","funders":"","keywords":"Monetary policy; Monetary economics; Central bank; Economics; Forward guidance; Financial market; Private information retrieval; Test (biology); Business; Inflation targeting; Finance; Credit channel; Computer science; Computer security","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":[0.002440266,0.0002653264,0.0004061837,0.002323865,0.0006551385,0.003981652,0.0004288257,0.002192739,0.02136955],"category_scores_gemma":[0.02389687,0.0003292582,0.0002390417,0.001769826,0.0004093777,0.003087434,0.0008743248,0.002094795,0.009092755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001207607,"about_ca_system_score_gemma":0.001205665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002610239,"about_ca_topic_score_gemma":0.002345208,"domain_scores_codex":[0.9985868,0.0002530986,0.00008387765,0.0001445848,0.000677518,0.0002541444],"domain_scores_gemma":[0.9785728,0.01213229,0.004199279,0.001184431,0.002997835,0.0009134932],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0041685,0.0007218919,0.06389926,0.0009343731,0.0001374714,0.004043517,0.00158425,0.00794326,0.006345144,0.1917854,0.3245206,0.3939163],"study_design_scores_gemma":[0.0004455044,0.0009402771,0.2388611,0.0008713915,0.0002736258,0.001302614,0.002141427,0.03948163,0.01707441,0.1393189,0.559044,0.0002451024],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3848716,0.009542203,0.01648328,0.06129406,0.006446502,0.0002265187,0.007975223,0.001971712,0.5111889],"genre_scores_gemma":[0.9477555,0.001992493,0.001523327,0.001375362,0.003260972,0.00003529567,0.001839406,0.00009810975,0.04211955],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02136955,"threshold_uncertainty_score":0.07148826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01398724783697239,"score_gpt":0.2139938112502076,"score_spread":0.2000065634132352,"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."}}