{"id":"W4389046557","doi":"10.3390/forecast5040036","title":"Macroeconomic Predictions Using Payments Data and Machine Learning","year":2023,"lang":"en","type":"article","venue":"Forecasting","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Overfitting; Nowcasting; Interpretability; Payment; Computer science; Econometrics; Value (mathematics); Machine learning; Economics; Artificial neural network","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007158637,0.00012795,0.0002472326,0.0002546943,0.0003279098,0.00008969507,0.000214606,0.00005786983,0.0002785082],"category_scores_gemma":[0.0001720872,0.0001604094,0.00003373804,0.0001535502,0.00003777049,0.0004791583,0.0003373852,0.0001708811,0.0004755584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005429869,"about_ca_system_score_gemma":0.000007029631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001004538,"about_ca_topic_score_gemma":0.00004397399,"domain_scores_codex":[0.998719,0.00001140653,0.000447592,0.0004323407,0.00001347549,0.0003761351],"domain_scores_gemma":[0.9992741,0.00006929267,0.000234228,0.0003266749,0.000002671472,0.00009302793],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001521153,0.00001994005,0.9371608,0.00005943403,0.0001575011,0.00001118817,0.0008204232,0.05062141,0.00003302519,0.00168122,0.001657722,0.007762079],"study_design_scores_gemma":[0.0002728663,0.00002237239,0.0108357,0.00001350604,0.000006759763,0.00003021904,0.0000548061,0.9709055,0.000005798036,0.002237415,0.01545878,0.0001563234],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924289,0.0005024134,0.00182744,0.0001619239,0.0003486221,0.0001143932,0.0009469741,0.0001222451,0.003547101],"genre_scores_gemma":[0.9973509,0.0001780377,0.0008105075,0.00006987853,0.0002173676,0.000004091565,0.0003234103,0.00003130965,0.001014553],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9263251,"threshold_uncertainty_score":0.6541304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3317320262824558,"score_gpt":0.2771811568458795,"score_spread":0.05455086943657628,"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."}}