{"id":"W4313423195","doi":"10.1101/2022.12.29.22284048","title":"Estimates of COVID-19 deaths in Mainland China after abandoning zero COVID policy","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institutes of Health","keywords":"Mainland China; Coronavirus disease 2019 (COVID-19); China; Case fatality rate; Demography; Population; Quarter (Canadian coin); Mainland; Geography; Medicine; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Socioeconomics; Environmental health; Disease; Infectious disease (medical specialty)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001232543,0.0004996113,0.0002073441,0.0009744373,0.0002463122,0.0004962864,0.0004103323,0.0001872931,0.001071677],"category_scores_gemma":[0.001711951,0.0001754198,0.0009025119,0.0008596347,0.0002192189,0.0004792762,0.0006920413,0.0003595342,0.0001846278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001809035,"about_ca_system_score_gemma":0.00156709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06761684,"about_ca_topic_score_gemma":0.05555862,"domain_scores_codex":[0.9997054,0.00006468298,0.00003142126,0.00006647467,0.00005669441,0.0000752876],"domain_scores_gemma":[0.9989116,0.000167887,0.0003624018,0.00009818541,0.0003236729,0.0001362605],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009231042,0.00001078372,0.978746,0.0001012557,0.0002077131,0.0001742581,0.0001940397,0.009699902,0.0002492438,0.0004077262,0.001617489,0.008499206],"study_design_scores_gemma":[0.00001001351,0.00006077294,0.9854965,0.00004850696,0.00008155486,0.00008491994,0.0003010794,0.01028304,0.0003977946,0.0002261471,0.002993631,0.0000161248],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9828588,0.0008805147,0.001856413,0.0002500738,0.00002711347,0.00004089829,0.01198272,0.0000527655,0.002050689],"genre_scores_gemma":[0.9867355,0.0004107803,0.0006755915,0.00007253456,0.00001627834,0.00005928058,0.01090787,0.000006954069,0.001115376],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06761684,"threshold_uncertainty_score":0.1344465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1594237062358537,"score_gpt":0.4392996928687273,"score_spread":0.2798759866328736,"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."}}