{"id":"W3014257517","doi":"10.1016/j.jcv.2020.104341","title":"Challenges of SARS-CoV-2 and lessons learnt from SARS in Guangdong Province, China","year":2020,"lang":"en","type":"article","venue":"Journal of Clinical Virology","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University; Impact","funders":"","keywords":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Coronavirus disease 2019 (COVID-19); China; 2019-20 coronavirus outbreak; Sars virus; Betacoronavirus; Virology; Geography; Medicine; Environmental health; Outbreak; Infectious disease (medical specialty); Disease; Internal medicine","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":[0.002084275,0.0003777137,0.0003831153,0.0006556889,0.001069894,0.001103517,0.0006154214,0.000832522,0.001842045],"category_scores_gemma":[0.002340154,0.0002321596,0.0004143947,0.00113706,0.001061077,0.001575249,0.001341325,0.001236024,0.0001095794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004132186,"about_ca_system_score_gemma":0.01340622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3052599,"about_ca_topic_score_gemma":0.3406433,"domain_scores_codex":[0.9992387,0.0002180488,0.00007149992,0.0001006294,0.00009883829,0.0002722854],"domain_scores_gemma":[0.9990723,0.000202377,0.0001505101,0.00004999495,0.0001709129,0.0003537825],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000175492,0.0002143427,0.8127941,0.001260631,0.0002027207,0.006132901,0.03708419,0.001672652,0.001508266,0.006080049,0.01777726,0.1150974],"study_design_scores_gemma":[0.0000318192,0.0002142525,0.8944724,0.001019653,0.000100515,0.001035381,0.06946751,0.001231723,0.0002225986,0.00427558,0.02786844,0.00005999118],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8929654,0.01657075,0.0004268785,0.08156992,0.0004865018,0.00004779871,0.0005344584,0.00001575251,0.00738262],"genre_scores_gemma":[0.984109,0.01060584,0.0004026016,0.003081909,0.0002302296,0.00001892156,0.0002949519,0.000003851167,0.001252759],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3052599,"threshold_uncertainty_score":0.6069661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6398384978464725,"score_gpt":0.5501262236204263,"score_spread":0.08971227422604622,"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."}}