{"id":"W3124007508","doi":"","title":"Nowcasting GDP with electronic payments data","year":2015,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nowcasting; Payment; Quarter (Canadian coin); Debit card; Payment card; Database transaction; Economics; Econometrics; Credit card; Business; Finance; Computer science; Geography; Database","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":[0.002480397,0.0004606917,0.0003647029,0.002119965,0.0001820362,0.0011387,0.0005827506,0.0007291669,0.002301035],"category_scores_gemma":[0.0189432,0.0002610882,0.0005953517,0.00234136,0.0004628351,0.0008923532,0.0009582375,0.001288681,0.0007233632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006564835,"about_ca_system_score_gemma":0.0003679577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009233497,"about_ca_topic_score_gemma":0.008124605,"domain_scores_codex":[0.9991524,0.0002656039,0.00006733192,0.0002263332,0.0002090387,0.00007928465],"domain_scores_gemma":[0.9884325,0.006499373,0.001543576,0.00191879,0.001359233,0.000246436],"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":[0.001552273,0.0002851549,0.2811169,0.0002136844,0.0002569256,0.0005451377,0.0004581005,0.5685642,0.003084106,0.01262341,0.01390332,0.1173969],"study_design_scores_gemma":[0.0001619191,0.0004975381,0.3042974,0.0001170688,0.0001110798,0.0002709772,0.0004567713,0.6399075,0.01315187,0.01337822,0.02749768,0.0001520146],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9520939,0.0002727208,0.02325519,0.0006271785,0.0003617228,0.0001158605,0.01851274,0.0005952229,0.004165547],"genre_scores_gemma":[0.9665364,0.0001627463,0.01001254,0.00004094043,0.0001104874,0.00005255618,0.02114297,0.00006732213,0.001874091],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009233497,"threshold_uncertainty_score":0.01835954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06406739751356566,"score_gpt":0.3137355365260569,"score_spread":0.2496681390124912,"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."}}