{"id":"W3164992042","doi":"","title":"Interest Rates, Money, and Economic Activity","year":2019,"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":"University of Calgary","funders":"","keywords":"Divisia monetary aggregates index; Divisia index; Economics; Econometrics; Granger causality; Monetary economics; Monetary policy; Work (physics); Industrial production; Asset (computer security); Causality (physics); Broad money; Macroeconomics; Central bank; Mathematics; Quantitative easing; Statistics; Computer science; Energy (signal processing)","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":[0.001403212,0.0003945555,0.0004116552,0.001544974,0.0003410986,0.002710183,0.0004542083,0.0009630633,0.003996824],"category_scores_gemma":[0.01662518,0.0001852641,0.0002397552,0.003734602,0.0007001777,0.002150993,0.0008449447,0.0009580448,0.001028339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006632813,"about_ca_system_score_gemma":0.0003236567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002116282,"about_ca_topic_score_gemma":0.001865054,"domain_scores_codex":[0.9992006,0.0003883925,0.0000821022,0.0001307949,0.0001370839,0.0000610616],"domain_scores_gemma":[0.9913447,0.003998682,0.00351127,0.0003775361,0.000463279,0.00030455],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005340248,0.0002928691,0.4464025,0.0005621685,0.0004109557,0.0009625097,0.001862912,0.02471068,0.001065178,0.3777571,0.009332751,0.1361064],"study_design_scores_gemma":[0.00007167368,0.0003769987,0.4790168,0.000610645,0.0003198119,0.001651851,0.001790418,0.03162122,0.001549382,0.3792885,0.1035218,0.0001809017],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.837995,0.04100474,0.02308512,0.009983646,0.0004892017,0.00006573064,0.003343535,0.0002052926,0.08382766],"genre_scores_gemma":[0.9836162,0.007120474,0.002190665,0.0002666646,0.0004225349,0.0000383809,0.0008934654,0.00002363557,0.005428015],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003996824,"threshold_uncertainty_score":0.01337069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03575588575857309,"score_gpt":0.2295733468132235,"score_spread":0.1938174610546504,"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."}}