{"id":"W4385484425","doi":"10.18235/0005004","title":"Which One Predicts Better?: Comparing Different GDP Nowcasting Methods Using Brazilian Data","year":2023,"lang":"en","type":"report","venue":"","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nowcasting; Econometrics; Computer science; Scalability; Quarter (Canadian coin); Machine learning; Artificial intelligence; Economics; 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":[0.01408867,0.0009198437,0.0009448658,0.001386723,0.0004678371,0.001559442,0.001101509,0.0009554611,0.0009140635],"category_scores_gemma":[0.04428223,0.0003234911,0.0009623161,0.001747382,0.0005757229,0.001998047,0.001033912,0.001489206,0.0003016539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001249787,"about_ca_system_score_gemma":0.001563677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09141655,"about_ca_topic_score_gemma":0.04130413,"domain_scores_codex":[0.9972481,0.001930427,0.0001538549,0.0003367596,0.0002221259,0.0001087791],"domain_scores_gemma":[0.9805839,0.01597284,0.000721211,0.001311423,0.001179443,0.000231094],"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":[0.001518394,0.0004623864,0.1701503,0.0007494822,0.001580749,0.0002227607,0.00111055,0.5631404,0.00137612,0.02099718,0.01182944,0.2268623],"study_design_scores_gemma":[0.0001372358,0.0002005604,0.04295547,0.0002695221,0.0002066043,0.00006685731,0.000665792,0.9368254,0.001187953,0.0119387,0.005474881,0.00007106886],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.897009,0.006303561,0.07587244,0.006681065,0.0006179234,0.0001720874,0.004045882,0.0009020018,0.008396],"genre_scores_gemma":[0.9749777,0.001238271,0.01850128,0.0001895746,0.0001343996,0.00003779903,0.004216611,0.0001091513,0.0005953306],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09141655,"threshold_uncertainty_score":0.1817689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6878607446888738,"score_gpt":0.4172995132623321,"score_spread":0.2705612314265418,"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."}}