{"id":"W2942581885","doi":"","title":"Nowcasting US GDP Growth in `Pseudo\\' Real Time Using Various Econometric Models","year":2019,"lang":"en","type":"article","venue":"","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nowcasting; Econometrics; Real gross domestic product; Gross domestic product; Lasso (programming language); Econometric model; Quarter (Canadian coin); Dynamic factor; Economics; Computer science; Macroeconomics; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004192072,0.0006140624,0.0006123062,0.0006165504,0.0001830563,0.001095414,0.0007091803,0.0006203339,0.001281497],"category_scores_gemma":[0.01138675,0.0002608956,0.0008812996,0.0009026522,0.0004398,0.001204292,0.0005990238,0.001221574,0.0002614337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005115153,"about_ca_system_score_gemma":0.0007322019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00559133,"about_ca_topic_score_gemma":0.005346217,"domain_scores_codex":[0.9990557,0.0006290382,0.00004282598,0.0001157166,0.0001129391,0.0000438363],"domain_scores_gemma":[0.9960631,0.003071133,0.0003180214,0.000237781,0.0002515365,0.00005860473],"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":[0.0001562358,0.00005544164,0.004621508,0.00009393053,0.000105167,0.00004521991,0.00009367843,0.9035393,0.0007085967,0.02053528,0.0009808202,0.06906487],"study_design_scores_gemma":[0.000006163352,0.00001866909,0.0007074855,0.000008752833,0.00000916537,0.000006758532,0.00001422603,0.9944767,0.0002410107,0.004172268,0.0003304273,0.000008487923],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1869935,0.0007517982,0.80818,0.0009202865,0.0001309418,0.00006021499,0.0005605334,0.0004306703,0.00197217],"genre_scores_gemma":[0.8014102,0.001074529,0.1932915,0.0001399184,0.0001235162,0.0001099293,0.001599954,0.00008017479,0.002170256],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00559133,"threshold_uncertainty_score":0.02217007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1488669466035495,"score_gpt":0.3624562357587408,"score_spread":0.2135892891551913,"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."}}