{"id":"W3123884394","doi":"","title":"Identifying a Policymaker's Target: An Application to the Bank of Canada","year":2002,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Uncorrelated; Inflation (cosmology); Inflation targeting; Monetary policy; Economics; Test (biology); Bank rate; Monetary economics; Central bank; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.006328518,0.0006321209,0.0009265168,0.001438944,0.004269331,0.00304878,0.001461223,0.001829432,0.004198353],"category_scores_gemma":[0.03320264,0.0002547461,0.0006874013,0.004493548,0.001333816,0.001001155,0.00145284,0.001769726,0.0003265313],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03292241,"about_ca_system_score_gemma":0.04589231,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.984453,"about_ca_topic_score_gemma":0.9755679,"domain_scores_codex":[0.9971117,0.0009041947,0.00008918517,0.0003844665,0.0009432358,0.0005673232],"domain_scores_gemma":[0.9861035,0.007618988,0.0008537799,0.0004181188,0.004171045,0.0008345729],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001344819,0.0005423327,0.4030562,0.0004645514,0.0006231731,0.001784347,0.004656594,0.1738617,0.001827933,0.2085858,0.058512,0.1447406],"study_design_scores_gemma":[0.0009099262,0.0003003352,0.1547611,0.0001467493,0.0005611956,0.000296564,0.006637712,0.7465662,0.003336819,0.05028916,0.03589407,0.0003001296],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8525122,0.002916484,0.04592148,0.01934952,0.0003163678,0.0005792536,0.00424739,0.0008350763,0.07332228],"genre_scores_gemma":[0.9785039,0.0007174332,0.01357312,0.0004839306,0.00004949347,0.00008070012,0.0006457546,0.00004343301,0.005902343],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9670776,"threshold_uncertainty_score":0.23887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03310544205855494,"score_gpt":0.2176289662626739,"score_spread":0.184523524204119,"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."}}