{"id":"W4377832331","doi":"10.1257/pandp.20231117","title":"News Media, Inflation, and Sentiment","year":2023,"lang":"en","type":"article","venue":"AEA Papers and Proceedings","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Inflation (cosmology); Narrative; Social media; Economics; Sentiment analysis; Monetary economics; Real interest rate; Keynesian economics; Monetary policy; Political science; Computer science; Linguistics; Artificial intelligence; Law","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":[0.0007070704,0.0002186128,0.0001885465,0.001948834,0.0003995556,0.002038458,0.000152676,0.0003906963,0.003674306],"category_scores_gemma":[0.01132856,0.0001257896,0.0001743604,0.002926863,0.0003555377,0.001344636,0.0005298066,0.0005621306,0.0006866339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004313679,"about_ca_system_score_gemma":0.0002003425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002319207,"about_ca_topic_score_gemma":0.002445796,"domain_scores_codex":[0.9995139,0.0001853765,0.00003509513,0.00005810069,0.00014209,0.00006537353],"domain_scores_gemma":[0.9837897,0.008832984,0.005829889,0.0002370739,0.000789677,0.0005206923],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003083551,0.0003120821,0.9501446,0.0002069768,0.0001705974,0.0002907322,0.001939183,0.00063729,0.001417606,0.00599704,0.004053601,0.03452194],"study_design_scores_gemma":[0.00001748665,0.000115418,0.9785685,0.0000892724,0.0001021394,0.0002344441,0.002188894,0.004288724,0.000798963,0.005881789,0.007690601,0.00002384982],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9790055,0.001169743,0.000698717,0.001474829,0.00007514287,0.0000148662,0.001410664,0.00001784628,0.01613276],"genre_scores_gemma":[0.9970819,0.0006473397,0.0002841362,0.0001393226,0.0002348954,0.00001247866,0.0006101427,0.000008229706,0.0009814793],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003674306,"threshold_uncertainty_score":0.01229173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01704074917151296,"score_gpt":0.20332629232548,"score_spread":0.186285543153967,"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."}}