{"id":"W4225712666","doi":"10.1016/j.isatra.2021.12.004","title":"Lessons drawn from China and South Korea for managing COVID-19 epidemic: Insights from a comparative modeling study","year":2021,"lang":"en","type":"article","venue":"ISA Transactions","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":56,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Mainland China; China; Geography; Psychological intervention; Outbreak; Demography; Coronavirus disease 2019 (COVID-19); Basic reproduction number; Reproduction; Confidence interval; Transmission (telecommunications); Mainland; Socioeconomics; Statistics; Medicine; Biology; Ecology; Population; Computer science; Disease; Mathematics; Virology; Infectious disease (medical specialty); Sociology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00031293,0.0003208473,0.0008965019,0.0000747749,0.001186141,0.00008869029,0.0001658892,0.0001224163,0.000114054],"category_scores_gemma":[0.001180396,0.0002746631,0.0002123294,0.0002231271,0.0001445745,0.0001394837,0.00004395405,0.0003533976,0.000007178399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001719399,"about_ca_system_score_gemma":0.0001331057,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004168686,"about_ca_topic_score_gemma":0.009921877,"domain_scores_codex":[0.99768,0.000404131,0.0006115898,0.0007925015,0.0001872132,0.0003245648],"domain_scores_gemma":[0.9918308,0.007289291,0.0001431315,0.0004113209,0.00008876207,0.0002367245],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0008764338,0.005001802,0.01724086,0.0006071543,0.007638846,0.0002042017,0.7549264,0.1706969,0.002425714,0.03248573,0.002062806,0.005833073],"study_design_scores_gemma":[0.00250588,0.000101522,0.004062255,0.00008162521,0.0009758713,0.000002791108,0.0449512,0.2525879,0.0001026163,0.6928766,0.001196103,0.0005556296],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.385691,0.0005763345,0.6080928,0.00432169,0.00009303544,0.0005667572,0.0004182643,0.0001484767,0.00009166364],"genre_scores_gemma":[0.9759697,0.00007472643,0.02271288,0.0006985122,0.00009431061,0.0002961268,0.00004318418,0.00002703286,0.00008350122],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7099752,"threshold_uncertainty_score":0.9999706,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4621305008893982,"score_gpt":0.4728471989288142,"score_spread":0.01071669803941599,"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."}}