{"id":"W4323542695","doi":"10.14745/ccdr.v49i23a01","title":"Event-based surveillance: Providing early warning for communicable disease threats","year":2023,"lang":"en","type":"article","venue":"Canada Communicable Disease Report","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Agency of Canada","funders":"Public Health Agency; Public Health Agency of Canada","keywords":"Public health; Communicable disease; Warning system; Pandemic; Context (archaeology); Environmental health; Disease surveillance; Public health surveillance; Disease; Population; Non-communicable disease; Medicine; Coronavirus disease 2019 (COVID-19); Infectious disease (medical specialty); Geography; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001568991,0.0005696515,0.001097679,0.0002257012,0.0009806519,0.0001302649,0.001101587,0.00009887635,0.0001229241],"category_scores_gemma":[0.003532729,0.0005877364,0.0004348063,0.001215441,0.0002384705,0.0002500283,0.0006547863,0.0005276729,0.00003090382],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008898248,"about_ca_system_score_gemma":0.01243821,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.06656756,"about_ca_topic_score_gemma":0.0882264,"domain_scores_codex":[0.9950942,0.0004152351,0.001122012,0.0008752768,0.001224141,0.001269122],"domain_scores_gemma":[0.9893957,0.001027171,0.0005283765,0.005878932,0.000812998,0.002356785],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002316127,0.0004693533,0.8751461,0.001660769,0.0004294521,0.009931596,0.00004223308,0.004848273,0.0001597835,0.0001665299,0.1027005,0.002129274],"study_design_scores_gemma":[0.004245337,0.0001186334,0.659569,0.001091731,0.0004713587,0.00005127717,0.0002200377,0.04419195,0.00007502277,0.0002783231,0.2885465,0.001140821],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9517298,0.01291847,0.0008190742,0.01319586,0.001161306,0.006727469,0.006441358,0.002691899,0.004314757],"genre_scores_gemma":[0.979607,0.000262167,0.0004274553,0.001122318,0.0001313886,0.0009164031,0.01296369,0.0001903902,0.004379216],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2155771,"threshold_uncertainty_score":0.9996574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03650952109167818,"score_gpt":0.3158148498787824,"score_spread":0.2793053287871042,"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."}}