{"id":"W4399774164","doi":"10.1080/02664763.2024.2351467","title":"Identifying waves of COVID-19 mortality using skew normal curves","year":2024,"lang":"en","type":"article","venue":"Journal of Applied Statistics","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Global Health Research; St. Michael's Hospital; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Skew; Coronavirus disease 2019 (COVID-19); Demography; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Econometrics; Statistics; Geography; Mathematics; Medicine; Computer science; Telecommunications; Internal medicine; Outbreak; Sociology; Virology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002762799,0.0002050594,0.0007961533,0.0001384271,0.0001188319,0.00004378642,0.0002546703,0.0001139131,0.0001725852],"category_scores_gemma":[0.006613872,0.0001553758,0.0001683752,0.0002641622,0.0002104947,0.00009434931,0.0001580036,0.0005438929,0.000004553807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002430332,"about_ca_system_score_gemma":0.0003586634,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005109028,"about_ca_topic_score_gemma":0.00002619398,"domain_scores_codex":[0.997384,0.0001207504,0.001424617,0.0001902681,0.0006084303,0.0002719295],"domain_scores_gemma":[0.9923765,0.006208659,0.0008319228,0.0001937341,0.0001912273,0.0001979368],"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":[0.0001718866,0.0003055216,0.003441426,0.022673,0.001530992,0.0006185288,0.003081837,0.001339546,0.003882844,0.8731995,0.08646879,0.003286115],"study_design_scores_gemma":[0.0003485089,0.0001006911,0.002164838,0.0006582459,0.0007430306,0.00006019471,0.000462019,0.003132776,0.0004093067,0.9881847,0.003483341,0.0002523743],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.047811,0.002344604,0.948001,0.0004121104,0.0003766557,0.0002041136,0.0002956663,0.00004299561,0.0005118123],"genre_scores_gemma":[0.5841999,0.001897461,0.412403,0.001054244,0.0003420107,0.000004416906,0.000006656284,0.00004162954,0.00005072886],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5363889,"threshold_uncertainty_score":0.7917901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4137236397416159,"score_gpt":0.5089745621759725,"score_spread":0.09525092243435662,"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."}}