{"id":"W6913270528","doi":"10.5683/sp3/cxdocf","title":"Replication Data and Code for: Monetary and fiscal policies in a heterogeneous-agent economy","year":2022,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Replication (statistics); Replicate; Code (set theory); Data file; Fiscal policy; Table (database)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.001392178,0.001825313,0.001262435,0.002235019,0.0007896511,0.002653508,0.002841801,0.002351152,0.1363408],"category_scores_gemma":[0.01004023,0.0009211071,0.001457694,0.004800577,0.0004610623,0.001330603,0.00140959,0.002034389,0.1048633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001939887,"about_ca_system_score_gemma":0.003283342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04549702,"about_ca_topic_score_gemma":0.06075273,"domain_scores_codex":[0.9991209,0.0002075795,0.00009369326,0.0002666147,0.0001699169,0.0001412422],"domain_scores_gemma":[0.9970273,0.0009117117,0.0002933652,0.0008673411,0.000657807,0.0002423748],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004835175,0.00001515755,0.0006581267,0.0001998991,0.00002421419,0.00001133255,0.00001233252,0.0005500531,0.00003047416,0.0007737626,0.9965914,0.00108489],"study_design_scores_gemma":[0.001058048,0.00002449305,0.006617186,0.0003197731,0.0000609813,0.00008533729,0.00009724694,0.002404627,0.000424288,0.006925994,0.9819146,0.00006741612],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001678167,0.00004022415,0.0001049271,0.0001007364,0.00002994535,0.00001032956,0.9983926,0.0004220565,0.0007312679],"genre_scores_gemma":[0.001671063,0.00004877406,0.0005133182,0.00009982318,0.00001586422,0.0001274605,0.9960962,0.0002255305,0.001202042],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1363408,"threshold_uncertainty_score":0.4561055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05708703909195367,"score_gpt":0.3162452601825042,"score_spread":0.2591582210905505,"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."}}