{"id":"W3125747825","doi":"10.2139/ssrn.3570117","title":"Impacts on the U.S. Macroeconomy of Mandatory Business Closures in Response to the COVID-19 Pandemic","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Impact","funders":"","keywords":"Computable general equilibrium; Coronavirus disease 2019 (COVID-19); Economics; Closure (psychology); Order (exchange); Pandemic; Fiscal year; Demographic economics; Macroeconomics; Finance","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008488444,0.0002110657,0.0004106667,0.0003020854,0.0001918019,0.00007219378,0.0008364751,0.0001001986,0.00019659],"category_scores_gemma":[0.005470577,0.0001504923,0.0001356904,0.0007423728,0.00008607798,0.0001575625,0.0001019107,0.001547924,0.0002414371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002178871,"about_ca_system_score_gemma":0.002936799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005048826,"about_ca_topic_score_gemma":0.001534506,"domain_scores_codex":[0.9970956,0.0002134702,0.0007835642,0.0003276536,0.00009555444,0.001484091],"domain_scores_gemma":[0.9979414,0.0008479766,0.0005122465,0.0003879795,0.00004107254,0.0002693235],"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":[0.005769186,0.0001470747,0.7599574,0.00006850869,0.0003447933,0.00002328438,0.007592256,0.009017798,0.000595009,0.2039208,0.009595174,0.002968669],"study_design_scores_gemma":[0.004612696,0.001364831,0.2433529,0.00006226714,0.00002881317,0.0003866412,0.002616741,0.0004480015,0.00008297351,0.2109735,0.5352832,0.0007874731],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8745198,0.002928132,0.002416296,0.1191865,0.0001552473,0.000371941,0.00004985662,0.00001968861,0.0003524699],"genre_scores_gemma":[0.9721589,0.001804331,0.000007646794,0.02563654,0.0002122545,0.00001433236,0.00000156724,0.0000301281,0.0001342871],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5256881,"threshold_uncertainty_score":0.6725044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05071359208487155,"score_gpt":0.2807408819138075,"score_spread":0.230027289828936,"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."}}