{"id":"W3168870653","doi":"10.1016/j.econlet.2021.109938","title":"A century of Economic Policy Uncertainty through the French–Canadian lens","year":2021,"lang":"en","type":"article","venue":"Economics Letters","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke; HEC Montréal","funders":"Institut de Valorisation des Données; Canada First Research Excellence Fund; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Nowcasting; Index (typography); Relevance (law); Construct (python library); Security token; Political science; Economics; Regional science; Geography; Computer science; Meteorology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.007890241,0.0005498388,0.0009542015,0.003456469,0.01204429,0.02209508,0.001314857,0.006936923,0.008820672],"category_scores_gemma":[0.02596839,0.0003705182,0.0005483956,0.004651994,0.01486651,0.007304454,0.002713575,0.007712525,0.0004260353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1193,"about_ca_system_score_gemma":0.06290554,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9287987,"about_ca_topic_score_gemma":0.8979341,"domain_scores_codex":[0.9937268,0.001286733,0.0001725058,0.0006351849,0.002871448,0.001307207],"domain_scores_gemma":[0.9864511,0.005960915,0.0008372128,0.0005209409,0.004874121,0.001355581],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00008240222,0.00001569448,0.001499896,0.00006337719,0.00003384116,0.0002054285,0.003691004,0.002391466,0.0001301721,0.9150047,0.05403509,0.02284687],"study_design_scores_gemma":[0.00001986758,0.00001541184,0.007873652,0.0004214139,0.00003015357,0.0001422664,0.006535033,0.003373445,0.0002037224,0.3130436,0.6681862,0.0001552116],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02939034,0.04508224,0.005770641,0.7259048,0.002954219,0.00001453818,0.000669968,0.00008544572,0.1901278],"genre_scores_gemma":[0.9061443,0.02064131,0.002006449,0.04084094,0.004033267,0.00002090892,0.0001508075,0.000124332,0.02603765],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1193,"threshold_uncertainty_score":0.865586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01791497402467557,"score_gpt":0.2087854586146703,"score_spread":0.1908704845899948,"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."}}