{"id":"W2336543819","doi":"","title":"A Mixed Frequency Approach to Forecast Private Consumption with ATM/POS Data","year":2016,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nowcasting; Private consumption; Quarter (Canadian coin); Payment; Consumption (sociology); Computer science; Variable (mathematics); Econometrics; Economics; Geography; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.004474169,0.0006722391,0.001437591,0.001286181,0.0002565259,0.0004798014,0.00282583,0.0007474648,0.0001822969],"category_scores_gemma":[0.0005348196,0.0007096088,0.0001815248,0.0002276279,0.0004277658,0.0005172741,0.003464497,0.001510319,0.0005090958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001855876,"about_ca_system_score_gemma":0.0003523494,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001925784,"about_ca_topic_score_gemma":0.0006560957,"domain_scores_codex":[0.9935032,0.0001475746,0.001696492,0.002970364,0.0001163412,0.001566009],"domain_scores_gemma":[0.9940816,0.000341768,0.0007328651,0.004274759,0.0000774139,0.0004915714],"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":[0.001298868,0.001500583,0.5649902,0.00179128,0.001250004,0.00008476898,0.001429351,0.008005382,0.00006800416,0.1232988,0.00167715,0.2946057],"study_design_scores_gemma":[0.01308381,0.00133465,0.1443967,0.003197569,0.0001185704,0.0002178792,0.000885124,0.1597211,0.0002148654,0.2607735,0.4043081,0.0117481],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5140989,0.0002305207,0.001033081,0.0005857068,0.0008372904,0.002166523,0.002058801,0.000113356,0.4788758],"genre_scores_gemma":[0.9660842,0.01042737,0.0188095,0.0001758199,0.0006911923,0.0007423395,0.001038651,0.0003400972,0.001690852],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.477185,"threshold_uncertainty_score":0.9995355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1425162166806923,"score_gpt":0.2967308791366852,"score_spread":0.1542146624559929,"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."}}