{"id":"W3099033854","doi":"10.1016/j.tmaid.2020.101918","title":"Changed transmission epidemiology of COVID-19 at early stage: A nationwide population-based piecewise mathematical modelling study","year":2020,"lang":"en","type":"letter","venue":"Travel Medicine and Infectious Disease","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"National Key Research and Development Program of China; Science and Technology Commission of Shanghai Municipality; National Natural Science Foundation of China","keywords":"Coronavirus disease 2019 (COVID-19); Epidemiology; Stage (stratigraphy); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Transmission (telecommunications); Piecewise; Population; Medicine; Virology; Computer science; Environmental health; Mathematics; Infectious disease (medical specialty); Biology; Outbreak; Disease; Internal medicine; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003182102,0.0002280842,0.0004347899,0.0003253028,0.0004179466,0.001039513,0.00103982,0.001477295,0.003568396],"category_scores_gemma":[0.01626158,0.0002918335,0.0009801773,0.0008562649,0.0002577082,0.001088681,0.0008329228,0.001915556,0.0004590616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001099014,"about_ca_system_score_gemma":0.001441952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04783931,"about_ca_topic_score_gemma":0.04744519,"domain_scores_codex":[0.9992298,0.0004924989,0.0000434699,0.00007881042,0.00006779676,0.00008769404],"domain_scores_gemma":[0.9952721,0.002671202,0.0006021287,0.0005798677,0.000582616,0.0002920456],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001554581,0.0004878416,0.8568304,0.0002740688,0.0006882812,0.001712178,0.002541145,0.0164932,0.0007034841,0.01059096,0.06004019,0.04808354],"study_design_scores_gemma":[0.0003336714,0.0009946764,0.7522863,0.0006117866,0.0009371791,0.003093068,0.006570548,0.1733881,0.0006776803,0.02431424,0.03662275,0.0001699201],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9058496,0.00102602,0.01304858,0.06674187,0.0003998072,0.00007918113,0.007234031,0.0001034712,0.005517401],"genre_scores_gemma":[0.9850181,0.0009981588,0.00556325,0.004280085,0.0001976902,0.00009539985,0.001437815,0.00004359542,0.002365983],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04783931,"threshold_uncertainty_score":0.09512174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2865439496298327,"score_gpt":0.422365081164846,"score_spread":0.1358211315350134,"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."}}