{"id":"W4324095240","doi":"10.3390/jrfm16030190","title":"Revisiting the Determinants of Consumption: A Bayesian Model Averaging Approach","year":2023,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Club; Econometrics; Consumption (sociology); Bayesian probability; Homogeneous; Convergence (economics); Economics; Construct (python library); Variable (mathematics); Bayesian inference; Panel data; Mathematics; Statistics; Computer science; Sociology; Economic growth; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006329495,0.0009412819,0.002358698,0.001643697,0.0005841687,0.001968031,0.001975479,0.001176697,0.002089106],"category_scores_gemma":[0.02006589,0.0009016181,0.001772419,0.002033542,0.0009027769,0.00282111,0.001241549,0.002129505,0.0003468379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008618696,"about_ca_system_score_gemma":0.001261352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01363862,"about_ca_topic_score_gemma":0.009993562,"domain_scores_codex":[0.9972087,0.0017342,0.0001160152,0.0004102177,0.0003839098,0.0001470226],"domain_scores_gemma":[0.9914346,0.006917956,0.0004728187,0.0006072409,0.0004759725,0.00009133565],"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":[0.0000659117,0.00009877152,0.008851268,0.0001571586,0.0005627152,0.000191367,0.0002987197,0.6642087,0.0007891506,0.2661429,0.00186826,0.05676509],"study_design_scores_gemma":[0.000007584728,0.00002860613,0.002005794,0.00002687341,0.00006356105,0.00003318676,0.00003329381,0.8688347,0.0001594905,0.1276457,0.001136047,0.00002498443],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04049945,0.0008931767,0.9552043,0.0006821376,0.00005038538,0.00003243614,0.0002351296,0.0001044261,0.002298561],"genre_scores_gemma":[0.8088511,0.003681839,0.1806804,0.0004201177,0.000399657,0.000230082,0.00112672,0.0001480503,0.004462081],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01363862,"threshold_uncertainty_score":0.03347397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05798087728966796,"score_gpt":0.2380498195297355,"score_spread":0.1800689422400675,"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."}}