{"id":"W4315978983","doi":"10.26509/frbc-wp-202306","title":"Post-COVID Inflation Dynamics: Higher for Longer","year":2023,"lang":"en","type":"report","venue":"Working paper","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Inflation (cosmology); Core inflation; Economics; Unemployment; Quarter (Canadian coin); Recession; Core (optical fiber); Econometrics; Goods and services; Coronavirus disease 2019 (COVID-19); Deflation; Keynesian economics; Macroeconomics; Monetary policy; Inflation targeting; Economy; Computer science; Geography; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001223254,0.0004083521,0.0008778802,0.0005083257,0.0002083994,0.0001674869,0.0003191727,0.000677904,0.002146727],"category_scores_gemma":[0.0002840036,0.000494178,0.0004816351,0.0001646357,0.00004551657,0.0002042668,0.00008216694,0.0003747192,0.002593847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001075226,"about_ca_system_score_gemma":0.0001293364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002066347,"about_ca_topic_score_gemma":0.0005682704,"domain_scores_codex":[0.9973356,0.00001222692,0.001145793,0.0007943608,0.00007113491,0.0006408734],"domain_scores_gemma":[0.9980311,0.0002154496,0.0009192524,0.0006504612,0.00004107381,0.000142658],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003094639,0.000213327,0.1343694,0.00201399,0.003024811,0.00005357077,0.001899272,0.009195305,0.00002032346,0.09140273,0.7038589,0.05363889],"study_design_scores_gemma":[0.0003530672,0.00004563127,0.01858122,0.00009824977,0.00003637534,0.000005716444,0.00001212531,0.002552673,0.000001023489,0.01005002,0.967631,0.0006329124],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01596156,0.009722723,0.001971238,0.006736038,0.03136766,0.002370154,0.005858329,0.0007818026,0.9252305],"genre_scores_gemma":[0.5565282,0.001790951,0.0007703161,0.002980694,0.006910106,0.0003548261,0.004189649,0.0004752735,0.426],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.5405666,"threshold_uncertainty_score":0.999751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.196036547422255,"score_gpt":0.3016660947349427,"score_spread":0.1056295473126877,"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."}}