{"id":"W3086411451","doi":"10.2196/19589","title":"Using WeChat, a Chinese Social Media App, for Early Detection of the COVID-19 Outbreak in December 2019: Retrospective Study","year":2020,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Outbreak; Social media; Coronavirus disease 2019 (COVID-19); Pandemic; Medicine; Index (typography); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); China; Demography; Virology; Geography; Internal medicine; Computer science; Disease; Sociology; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005996611,0.0001722557,0.0005553958,0.00009450247,0.0002174112,0.00001004144,0.00009978045,0.00009166719,0.000009368853],"category_scores_gemma":[0.0008694274,0.0001264562,0.00007938998,0.0005859726,0.00008805365,0.00007598859,0.00007029593,0.0002875703,0.000001747629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003450795,"about_ca_system_score_gemma":0.0009004966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001060289,"about_ca_topic_score_gemma":0.003361539,"domain_scores_codex":[0.9981901,0.0002226435,0.0004830953,0.0004050057,0.000336228,0.0003629281],"domain_scores_gemma":[0.9986427,0.000138366,0.0003086788,0.0002176808,0.0001018178,0.0005907543],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002914111,0.0004031782,0.9753869,0.001529525,0.00003018038,0.000006355522,0.01675242,0.000004161211,0.0002011331,0.00004553238,0.0007236451,0.002002873],"study_design_scores_gemma":[0.004655576,0.0005480949,0.9925925,0.00002275683,0.00006067488,0.000006436814,0.0009237009,0.000604763,0.000005880107,0.0001919855,0.0002915358,0.0000961535],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992878,0.0002333544,0.0003207075,0.003262852,0.0001799466,0.002628289,0.0003936186,0.00005920582,0.00004408652],"genre_scores_gemma":[0.9965135,0.00002975023,0.0001101305,0.002816223,0.0003760851,0.00009480188,0.00002538823,0.00002675593,0.000007342637],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01720556,"threshold_uncertainty_score":0.5156735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07865378927646081,"score_gpt":0.4105371500938845,"score_spread":0.3318833608174237,"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."}}