{"id":"W4319161940","doi":"10.5089/9798400231162.001","title":"Understanding Post-COVID Inflation Dynamics","year":2023,"lang":"en","type":"article","venue":"IMF Working Paper","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Inflation (cosmology); Dynamics (music); Economics; Virology; Keynesian economics; Medicine; Psychology; Physics; Outbreak; Astronomy; Internal medicine; Infectious disease (medical specialty)","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006471433,0.0001419083,0.0002236809,0.000415928,0.0001928381,0.0001204989,0.00017479,0.0001353261,0.0003377238],"category_scores_gemma":[0.0004412801,0.0001756044,0.00009101191,0.0007665696,0.00003738226,0.0002495563,0.00008568151,0.0001827921,0.001399905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001141547,"about_ca_system_score_gemma":0.00004753208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001725641,"about_ca_topic_score_gemma":0.0001754038,"domain_scores_codex":[0.998776,0.0000132842,0.0004045679,0.0003393764,0.00005561986,0.000411212],"domain_scores_gemma":[0.9991564,0.0002380888,0.0001934368,0.0003019963,0.00001275131,0.00009731129],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003733498,0.00002478496,0.480133,0.00005610208,0.00008533021,0.00002469686,0.002428482,0.005565875,0.0002804654,0.5046757,0.00347862,0.003209673],"study_design_scores_gemma":[0.002050507,0.0001013651,0.2197082,0.0001883493,0.0000243236,0.00001474706,0.001188315,0.09276506,0.0000356162,0.3293658,0.353191,0.001366745],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5467668,0.001118106,0.1168064,0.04622877,0.006963102,0.001171879,0.0002358681,0.002344979,0.2783641],"genre_scores_gemma":[0.9956564,0.0000852364,0.0001213287,0.002448979,0.0001759084,0.000009102297,0.00006607383,0.00004156222,0.001395387],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4488896,"threshold_uncertainty_score":0.9993776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1422547656265992,"score_gpt":0.2817600337289748,"score_spread":0.1395052681023756,"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."}}