{"id":"W4293801838","doi":"10.1007/s12546-022-09289-1","title":"Comparing COVID-19 fatality across countries: a synthetic demographic indicator","year":2022,"lang":"en","type":"article","venue":"Journal of Population Research","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Case fatality rate; Comparability; Coronavirus disease 2019 (COVID-19); Pandemic; Demography; Medicine; Population; Environmental health; Disease; Mathematics; Infectious disease (medical specialty)","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","sts"],"consensus_categories":[],"category_scores_codex":[0.02333418,0.0001366677,0.0005874755,0.0004320658,0.001744765,0.00007546676,0.0006483392,0.00007300366,0.0005805762],"category_scores_gemma":[0.02867927,0.0001101561,0.000222478,0.0008956696,0.0002838186,0.0001349673,0.0007813013,0.001287008,0.0000102355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001221423,"about_ca_system_score_gemma":0.0002150926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006204885,"about_ca_topic_score_gemma":0.0001687323,"domain_scores_codex":[0.9936688,0.002312287,0.001131264,0.0002630067,0.002063897,0.0005607662],"domain_scores_gemma":[0.9895751,0.008633424,0.0007731096,0.0003423241,0.0003232733,0.0003528101],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002584172,0.0002090359,0.971844,0.0002329342,0.000106523,0.00006383831,0.001581226,0.001380987,0.00002527081,0.01486193,0.009237173,0.0001987209],"study_design_scores_gemma":[0.001507195,0.0005426127,0.5978834,0.00006535315,0.00005201837,0.0001616167,0.005350016,0.001851243,0.00001243736,0.321592,0.07067665,0.0003054933],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9878698,0.0004660979,0.00241353,0.008616949,0.00015126,0.0003404488,0.0000352009,0.00003903197,0.00006766053],"genre_scores_gemma":[0.9983844,0.00006726311,0.0007532316,0.0005572906,0.0001253835,0.00003574081,0.000005296753,0.00001622808,0.00005521212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3739606,"threshold_uncertainty_score":0.9995548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.585671890002815,"score_gpt":0.5809995004093036,"score_spread":0.004672389593511461,"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."}}