{"id":"W4389579633","doi":"10.3386/w31954","title":"Time Use and Macroeconomic Uncertainty","year":2023,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Fiscal Policy and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Econometrics; Economics","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":[0.001005961,0.0002712811,0.0002945488,0.001036876,0.0003723578,0.001965173,0.0003632591,0.0006008974,0.002955477],"category_scores_gemma":[0.01227889,0.0001871914,0.0003349265,0.001886459,0.0005358554,0.001428067,0.001270188,0.0007837086,0.0002376094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00136523,"about_ca_system_score_gemma":0.0004278664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008558261,"about_ca_topic_score_gemma":0.00623011,"domain_scores_codex":[0.9992198,0.000249022,0.00005391876,0.0001180586,0.0002056785,0.0001534935],"domain_scores_gemma":[0.9892455,0.005697349,0.00379408,0.0003633254,0.0004617756,0.0004380012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003944821,0.0002639123,0.7310964,0.0001313317,0.0003158949,0.0005658417,0.001581175,0.1148469,0.0009965858,0.08869044,0.003426682,0.05769029],"study_design_scores_gemma":[0.00003457949,0.0003134661,0.6920666,0.0002001329,0.0002228545,0.0004584125,0.002632891,0.1284452,0.001952652,0.1485717,0.02494505,0.0001564008],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.958698,0.005165815,0.009680857,0.002921285,0.00006082416,0.00002477157,0.002316675,0.00003784558,0.02109392],"genre_scores_gemma":[0.9978673,0.0008345678,0.0003031529,0.0000467033,0.00003959328,0.000008523345,0.0003059487,0.000005518042,0.0005887205],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008558261,"threshold_uncertainty_score":0.01701689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5106944310937866,"score_gpt":0.474507457662448,"score_spread":0.0361869734313387,"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."}}