{"id":"W2756769458","doi":"","title":"Hand, foot and mouth disease in China: Evaluating an automated system for the detection of outbreaks","year":2014,"lang":"en","type":"article","venue":"QUT ePrints (Queensland University of Technology)","topic":"Animal Disease Management and Epidemiology","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"National Health and Medical Research Council; Medical Research Council; World Health Organization","keywords":"Outbreak; Medicine; Foot-and-mouth disease; Incidence (geometry); Disease; Public health; Disease surveillance; Epidemiology; Internal medicine; Virology; Pathology","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":[],"consensus_categories":[],"category_scores_codex":[0.0003962469,0.00007117353,0.00016831,0.00004381562,0.00016771,0.000004611544,0.000194039,0.00008823134,0.000006982811],"category_scores_gemma":[0.0001242037,0.00003267096,0.00004324304,0.0001553539,0.0001843224,0.00004360227,0.0001109181,0.00005711004,0.000001179883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001442157,"about_ca_system_score_gemma":0.000003125217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00119246,"about_ca_topic_score_gemma":0.0009900359,"domain_scores_codex":[0.9994403,0.00007025584,0.0001175365,0.000193553,0.00005277244,0.0001256561],"domain_scores_gemma":[0.9996246,0.0001028596,0.0001219927,0.00007419429,0.00003998847,0.00003638311],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009476797,0.0001255144,0.661796,0.0001680858,0.00006564416,0.000003227201,0.0001929364,0.000196575,0.05608731,0.005971299,0.00002286434,0.2744229],"study_design_scores_gemma":[0.0003560211,0.0001996817,0.942895,0.00002828932,0.00004973707,3.437152e-7,0.001257315,0.05395547,0.0002520926,0.0006706988,0.0002720046,0.00006336697],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982825,0.00004735331,0.0004886945,0.000714821,0.00002122427,0.0002548214,0.0000169718,0.0001065973,0.00006699946],"genre_scores_gemma":[0.9998171,0.000012058,0.0001255602,0.000005672487,0.00001104553,0.000001474014,0.000006949514,5.994628e-7,0.00001956016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.281099,"threshold_uncertainty_score":0.1802651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01755683804717971,"score_gpt":0.236041716638495,"score_spread":0.2184848785913153,"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."}}