{"id":"W4293794885","doi":"10.1080/10920277.2022.2100425","title":"Ensemble Economic Scenario Generators: Unity Makes Strength","year":2022,"lang":"en","type":"article","venue":"North American Actuarial Journal","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Econometrics; Sample (material); Bayesian probability; Ensemble forecasting; Economic model; Perspective (graphical); Bayesian inference; Economics; Machine learning; Artificial intelligence; Macroeconomics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007244228,0.0002850283,0.0006826463,0.0004231536,0.0009697331,0.0002521758,0.0005891328,0.00003605623,0.005640014],"category_scores_gemma":[0.00006043699,0.0003459833,0.0002851184,0.0002304752,0.0001511185,0.0003937356,0.0001647448,0.0008593545,0.0007117078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000849246,"about_ca_system_score_gemma":0.0001595214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004478776,"about_ca_topic_score_gemma":0.0008393216,"domain_scores_codex":[0.9976915,0.0001056194,0.0009812899,0.0004376863,0.00006613197,0.0007177974],"domain_scores_gemma":[0.9979319,0.00007369699,0.001166427,0.0004134462,0.000009836114,0.0004046792],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006136455,0.0004689515,0.7318348,0.00001131202,0.0008002875,0.0001164676,0.002677337,0.1191007,0.0000225055,0.007746441,0.07487605,0.06173148],"study_design_scores_gemma":[0.003371782,0.001757619,0.1958698,0.000004276946,0.00005547688,0.000878705,0.001040894,0.01901865,0.00008203143,0.006359753,0.7698629,0.001698093],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990492,0.00018858,0.0004691885,0.0007534841,0.00208878,0.0001392289,0.0006429243,0.00004110512,0.005184685],"genre_scores_gemma":[0.9951327,0.0001606704,0.000865389,0.001328686,0.002023212,0.00001622473,0.00005728953,0.0000473113,0.0003684611],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6949869,"threshold_uncertainty_score":0.9998992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04194995841847415,"score_gpt":0.2192080840466044,"score_spread":0.1772581256281302,"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."}}