{"id":"W4283330746","doi":"10.1016/j.sciaf.2022.e01257","title":"COVID -19 Morbidity and mortality in tropical countries: The effects of economic, institutional, and climatic variables","year":2022,"lang":"en","type":"article","venue":"Scientific African","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Ordinary least squares; Language change; 2019-20 coronavirus outbreak; Public health; Democracy; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Tropical disease; Disease; Epidemiology; Development economics; Geography; Economics; Socioeconomics; Infectious disease (medical specialty); Medicine; Political science; Outbreak; Econometrics; Virology; Politics","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":[0.00234722,0.0001023864,0.0003306572,0.00006314662,0.0007367234,0.00003874736,0.0002042241,0.00002571335,0.0001331997],"category_scores_gemma":[0.007093441,0.00006974271,0.00003608279,0.0002007483,0.001471117,0.00005085045,0.000527081,0.000141509,0.000001417342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003031328,"about_ca_system_score_gemma":0.0002342426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005029163,"about_ca_topic_score_gemma":0.0005998353,"domain_scores_codex":[0.9984922,0.0003844624,0.0003542106,0.0003496619,0.0002182097,0.0002012729],"domain_scores_gemma":[0.9939159,0.005527687,0.0001588746,0.0002818919,0.00001629173,0.00009939716],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000399752,0.0002062057,0.4788136,0.001149185,0.00007071161,0.00001388197,0.00406004,0.0003630685,0.0001219971,0.5072904,0.007762846,0.0001080012],"study_design_scores_gemma":[0.0009882512,0.0001682761,0.3508707,0.00003237119,0.0001052759,0.00001203155,0.002164434,0.003738669,0.00004217763,0.6034819,0.03812204,0.0002738372],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996686,0.0003782595,0.0003964093,0.001414104,0.0002966543,0.0004227756,0.00009588601,0.00002187567,0.0002879883],"genre_scores_gemma":[0.9992102,0.00004032374,0.0003091553,0.0002485361,0.00001537352,0.0001001136,0.00000297864,0.000003506047,0.00006974894],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.127943,"threshold_uncertainty_score":0.8492024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1376737434597573,"score_gpt":0.3837407476515329,"score_spread":0.2460670041917757,"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."}}