{"id":"W4382776049","doi":"10.2172/1986527","title":"Territorial Government Revenue Vulnerability Index (TGRVI): Measuring Financial Impacts to Territorial Governments during the COVID-19 Pandemic","year":2021,"lang":"en","type":"report","venue":"","topic":"Fiscal Policy and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cascades (Canada)","funders":"Argonne National Laboratory; Federal Emergency Management Agency; University of Chicago; U.S. Department of Energy","keywords":"Revenue; Index (typography); Government revenue; Vulnerability (computing); Government (linguistics); Vulnerability index; Business; Severance; Coronavirus disease 2019 (COVID-19); Tax revenue; Economics; Public economics; Finance; Labour 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":[0.0007995402,0.0004364089,0.0001786601,0.00159615,0.0003402642,0.0009876861,0.0003533931,0.0002876343,0.00345461],"category_scores_gemma":[0.003892722,0.0001178746,0.0002697076,0.00279196,0.0001922836,0.001055905,0.00127069,0.0007553091,0.001168601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002042939,"about_ca_system_score_gemma":0.002786244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09201732,"about_ca_topic_score_gemma":0.1158855,"domain_scores_codex":[0.9994299,0.00007916671,0.00003758574,0.0000389616,0.0002844085,0.0001300491],"domain_scores_gemma":[0.9978973,0.0001609344,0.0006880803,0.00005311946,0.0009861654,0.0002144597],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001569058,0.0001194384,0.4904852,0.0003430481,0.000143605,0.0002734764,0.0009059302,0.007735811,0.0004876882,0.009824261,0.4123477,0.07717691],"study_design_scores_gemma":[0.00001659162,0.000129211,0.8618796,0.0002429268,0.00005474204,0.0002738352,0.0027753,0.005423037,0.001035958,0.001746333,0.1263749,0.00004750092],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.5218395,0.001584833,0.002873159,0.004224322,0.0003538475,0.0003970689,0.3609048,0.0003407678,0.1074817],"genre_scores_gemma":[0.7450588,0.00263533,0.003246262,0.0003791469,0.0001233921,0.000375328,0.2309406,0.0001283431,0.01711286],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.09201732,"threshold_uncertainty_score":0.1829634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08152849722624024,"score_gpt":0.2823028419411623,"score_spread":0.2007743447149221,"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."}}