{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003287249,0.000645377,0.0007980239,0.002070301,0.0003143942,0.001502045,0.001361073,0.001222917,0.002844295],"category_scores_gemma":[0.01319246,0.0004988713,0.0009044976,0.001944232,0.0003058218,0.001425003,0.0007281944,0.0009850655,0.0005071377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004668957,"about_ca_system_score_gemma":0.0003738706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01222873,"about_ca_topic_score_gemma":0.008249253,"domain_scores_codex":[0.9985881,0.0007834595,0.00009295435,0.0002844569,0.0001697648,0.00008113052],"domain_scores_gemma":[0.9940356,0.004285149,0.0006789346,0.000548848,0.0003375459,0.0001139454],"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":[0.0008291513,0.0004014373,0.1265876,0.0001922123,0.0005998731,0.0004635917,0.000235998,0.7209089,0.002008936,0.02780176,0.003324781,0.1166459],"study_design_scores_gemma":[0.00001308483,0.00005508031,0.005357392,0.000009896654,0.00002393968,0.00003123828,0.00004061217,0.9874713,0.000276847,0.005671073,0.001034857,0.00001464789],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4597345,0.0007475559,0.531114,0.000919655,0.0002068751,0.0001429928,0.004014481,0.0005305648,0.002589425],"genre_scores_gemma":[0.9196773,0.0002707705,0.0743925,0.00008397547,0.0002192018,0.0001182665,0.003047826,0.00003755496,0.002152657],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01222873,"threshold_uncertainty_score":0.02431512,"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."}}