{"id":"W4362565039","doi":"10.1007/978-3-031-14197-3_8","title":"Using Natural Language Processing to Measure COVID-19-Induced Economic Policy Uncertainty for Canada and the USA","year":2023,"lang":"en","type":"book-chapter","venue":"Contributions to statistics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Index (typography); Coronavirus disease 2019 (COVID-19); Computer science; Artificial intelligence; Contraction (grammar); Natural language processing; Econometrics; Political science; Economics; Linguistics; Medicine","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":[0.001670954,0.0004209709,0.0002530401,0.003147576,0.001526166,0.003594796,0.0006388415,0.0004765116,0.00296675],"category_scores_gemma":[0.007357668,0.0001967082,0.000420571,0.004968537,0.00109297,0.001463518,0.0006501268,0.0009283353,0.0004794585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02373538,"about_ca_system_score_gemma":0.03083072,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9523223,"about_ca_topic_score_gemma":0.966256,"domain_scores_codex":[0.9990822,0.0001588561,0.00005676881,0.000120804,0.0004658908,0.0001153851],"domain_scores_gemma":[0.9962625,0.001725327,0.0002475861,0.0001428928,0.001517904,0.0001037869],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003711467,0.0001605266,0.07504845,0.0003842304,0.0001888863,0.0004134348,0.00328753,0.06744238,0.006373037,0.1292626,0.1477932,0.5692746],"study_design_scores_gemma":[0.00007122474,0.00008401543,0.2034023,0.0003307156,0.0001824907,0.0002361517,0.009056169,0.3670867,0.01463805,0.1484956,0.2560666,0.0003500236],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5578481,0.006646587,0.1534185,0.01903485,0.0007495749,0.0003781079,0.08502205,0.005692256,0.1712099],"genre_scores_gemma":[0.8859712,0.001863376,0.07353498,0.0007384314,0.00009838562,0.0001306481,0.02323896,0.0004661734,0.01395793],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0476777,"threshold_uncertainty_score":0.172213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05082941127230059,"score_gpt":0.3147193364294058,"score_spread":0.2638899251571052,"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."}}