{"id":"W3125684102","doi":"","title":"Is the MCI a Useful Signal of Monetary Policy Conditions? An Empirical Investigation","year":2000,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Balsillie School of International Affairs; Wilfrid Laurier University","funders":"","keywords":"Monetary policy; Credibility; Monetary economics; Economics; Transparency (behavior); Inflation targeting; Asset (computer security); Index (typography); Financial market; Interest rate; Exchange rate; Finance; Political science; Computer science","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":[0.01165755,0.0005832504,0.001341168,0.003972787,0.0009719728,0.004551101,0.001665906,0.001988621,0.01245943],"category_scores_gemma":[0.09633441,0.0003251883,0.0006590124,0.00551543,0.00289433,0.004612167,0.001958749,0.003200887,0.001871044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001289447,"about_ca_system_score_gemma":0.0008248696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007015894,"about_ca_topic_score_gemma":0.003327081,"domain_scores_codex":[0.9962568,0.002007407,0.0003693996,0.000440209,0.0006105978,0.0003156892],"domain_scores_gemma":[0.7627056,0.199194,0.02428447,0.005094989,0.005840815,0.002880252],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00258789,0.0009016771,0.9192013,0.0005443654,0.0005029672,0.0008940329,0.003830182,0.001577398,0.0008436572,0.01792716,0.003758377,0.047431],"study_design_scores_gemma":[0.000179027,0.0009895116,0.9494118,0.0003221744,0.0008347877,0.0005545249,0.0140103,0.01321089,0.0009031973,0.01042692,0.009073711,0.00008313778],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.980886,0.00178749,0.00104527,0.001287495,0.00005926269,0.00007793634,0.000625334,0.00002658792,0.01420461],"genre_scores_gemma":[0.9979354,0.0004262637,0.0002929857,0.0001032545,0.0001292582,0.00002711633,0.000441769,0.00000981978,0.0006341246],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01245943,"threshold_uncertainty_score":0.06165177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05488922992666535,"score_gpt":0.2692446713368724,"score_spread":0.214355441410207,"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."}}