{"id":"W3125041871","doi":"10.2139/ssrn.3678835","title":"The Impacts of the Coronavirus on the Economy of the United States","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Impact","funders":"","keywords":"Computable general equilibrium; Coronavirus disease 2019 (COVID-19); China; Workforce; Resilience (materials science); Economic impact analysis; Pandemic; Economics; Business; Economic growth; Geography; Macroeconomics; Medicine; Microeconomics","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":[0.000657859,0.0002537177,0.0002795785,0.000808634,0.0004452379,0.002183893,0.0001705772,0.0009479794,0.003881196],"category_scores_gemma":[0.003081466,0.0001487736,0.0004110779,0.001117114,0.00059998,0.001607506,0.0008054558,0.001139539,0.0002286959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001954305,"about_ca_system_score_gemma":0.001223071,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03763727,"about_ca_topic_score_gemma":0.03301658,"domain_scores_codex":[0.9997054,0.0001287283,0.00001067572,0.00001868808,0.0000584269,0.00007806559],"domain_scores_gemma":[0.9989803,0.0005011071,0.0001935312,0.00002988797,0.0001612178,0.0001339242],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0009273193,0.0005509065,0.3251847,0.0005256822,0.0006255443,0.002793791,0.0009466923,0.1604121,0.003152842,0.3288266,0.08875003,0.08730385],"study_design_scores_gemma":[0.00007566912,0.0005299725,0.5618331,0.0004891945,0.0004051514,0.0004399765,0.005886362,0.07966939,0.00153773,0.260781,0.08821809,0.0001342012],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8399982,0.02007084,0.001362511,0.04306474,0.0007598167,0.00002331212,0.003583515,0.00002981591,0.09110722],"genre_scores_gemma":[0.9850814,0.009895184,0.0001035132,0.0008299283,0.0002084488,0.000005701775,0.000370517,0.000007154561,0.003498153],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03763727,"threshold_uncertainty_score":0.07483637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03772407952410665,"score_gpt":0.2503992026120443,"score_spread":0.2126751230879377,"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."}}