{"id":"W2611898996","doi":"10.2196/publichealth.7313","title":"Saúde na Copa: The World’s First Application of Participatory Surveillance for a Mass Gathering at FIFA World Cup 2014, Brazil","year":2017,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Skoll Foundation","keywords":"Context (archaeology); Medicine; Disease surveillance; Public health; Public health surveillance; Social media; International Health Regulations; Environmental health; Internet privacy; Business; Disease; Computer science; Geography; World Wide Web; Coronavirus disease 2019 (COVID-19); Infectious disease (medical specialty)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007015256,0.0007640368,0.0003896829,0.001226311,0.007082264,0.003126398,0.001343173,0.001200324,0.005460013],"category_scores_gemma":[0.01344241,0.000539201,0.0007470652,0.0009917165,0.003136659,0.002161866,0.004960618,0.001627826,0.00101289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003338836,"about_ca_system_score_gemma":0.007903623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06280757,"about_ca_topic_score_gemma":0.1655766,"domain_scores_codex":[0.9957919,0.002626639,0.0001000984,0.0003919753,0.000503158,0.0005861371],"domain_scores_gemma":[0.9929543,0.003140528,0.0004562617,0.0007580153,0.001290413,0.001400349],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0004093185,0.001074533,0.0398687,0.002201494,0.00009621473,0.006436172,0.6354738,0.0004946666,0.007660903,0.00654945,0.04958131,0.2501534],"study_design_scores_gemma":[0.000130654,0.001362653,0.09894174,0.001998032,0.0001027338,0.001401088,0.3939565,0.002472998,0.003551846,0.003494198,0.4923828,0.0002047506],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8285638,0.003244399,0.0247459,0.02110817,0.001238484,0.00574712,0.002524466,0.001523053,0.1113046],"genre_scores_gemma":[0.934824,0.002200719,0.03473479,0.002531455,0.0002357597,0.002605238,0.0008782054,0.00041298,0.02157677],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06280757,"threshold_uncertainty_score":0.1248839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04689767392779711,"score_gpt":0.3581855211249667,"score_spread":0.3112878471971696,"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."}}