{"id":"W2903850923","doi":"10.1016/j.ijforecast.2019.09.006","title":"A three-frequency dynamic factor model for nowcasting Canadian provincial GDP growth","year":2020,"lang":"en","type":"article","venue":"International Journal of Forecasting","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"Bank of Canada","funders":"","keywords":"Nowcasting; Gross domestic product; Dynamic factor; Econometrics; Real gross domestic product; Economics; National accounts; Lag; Product (mathematics); Geography; Macroeconomics; Computer science; Mathematics; Meteorology","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":[0.001532029,0.0009602595,0.001077204,0.001079982,0.001940267,0.002524086,0.003103503,0.002364668,0.003953751],"category_scores_gemma":[0.004917793,0.0007598863,0.001128361,0.002128512,0.001017752,0.001406857,0.0007228822,0.002388211,0.000561843],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01215557,"about_ca_system_score_gemma":0.01286187,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9478424,"about_ca_topic_score_gemma":0.8820627,"domain_scores_codex":[0.9995097,0.00009545047,0.00002245152,0.0001254495,0.0001011437,0.0001458127],"domain_scores_gemma":[0.9988596,0.0003365287,0.00009221022,0.00005975131,0.0005411619,0.0001107549],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007550575,0.00002415791,0.002362901,0.00002426547,0.00004091224,0.00007012505,0.00007565034,0.9777008,0.0003154958,0.0110717,0.002259744,0.005978839],"study_design_scores_gemma":[0.00001040271,0.000003941225,0.0007166927,0.000003893433,0.00001121721,0.000005365129,0.00001747825,0.9973917,0.00004070412,0.001263714,0.0005201219,0.00001476201],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5624092,0.003100812,0.3832438,0.009273314,0.001533768,0.0002599115,0.009736324,0.001935558,0.0285072],"genre_scores_gemma":[0.9687899,0.0008617502,0.01578566,0.0001575347,0.0001218773,0.00007457752,0.001849284,0.00008126997,0.01227828],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9878444,"threshold_uncertainty_score":0.1049294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1563857037210321,"score_gpt":0.2518952886839546,"score_spread":0.09550958496292244,"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."}}