{"id":"W3049091859","doi":"10.1016/j.puhe.2020.08.008","title":"Policy determinants of COVID-19 pandemic–induced fatality rates across nations","year":2020,"lang":"en","type":"article","venue":"Public Health","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"Thompson Rivers University","funders":"","keywords":"Case fatality rate; Pandemic; Coronavirus disease 2019 (COVID-19); Mortality rate; Demography; Destinations; Development economics; Geography; Economic growth; Demographic economics; Political science; Medicine; Economics; Disease; Population; Sociology; Tourism; Infectious disease (medical specialty); Law","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00377285,0.0001961018,0.0007842816,0.0000825841,0.0004686482,0.00003087224,0.0003972047,0.0001238999,0.00005348525],"category_scores_gemma":[0.1386698,0.0001564389,0.0001252576,0.0009694247,0.000164264,0.0001358514,0.0003787548,0.0002421732,0.00001938567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006019145,"about_ca_system_score_gemma":0.002058647,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003864227,"about_ca_topic_score_gemma":0.002064081,"domain_scores_codex":[0.996824,0.0006858099,0.001001001,0.0004231605,0.0003007783,0.0007652969],"domain_scores_gemma":[0.9925209,0.005371762,0.0005938486,0.0003616287,0.0001557576,0.0009960964],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002232295,0.0002895549,0.8959518,0.002305221,0.0000679718,0.000003620961,0.01480594,0.000003775881,0.00006977982,0.06459656,0.006460274,0.01542319],"study_design_scores_gemma":[0.00395704,0.00118403,0.507462,0.0001129903,0.00003404455,0.0000282065,0.007986229,0.002692554,0.0001812686,0.2736298,0.2014372,0.001294629],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.743893,0.000112594,0.006404053,0.2479103,0.00006380599,0.0006711906,0.0003315918,0.000328702,0.0002847833],"genre_scores_gemma":[0.9648254,0.0001612558,0.001119269,0.03361146,0.0001633671,0.00005879339,0.00001209959,0.00001651952,0.00003182411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3884898,"threshold_uncertainty_score":0.8685855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7238012442112686,"score_gpt":0.594648659194429,"score_spread":0.1291525850168396,"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."}}