{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01566407,0.001139912,0.000738946,0.005394813,0.0008733378,0.00407559,0.002582591,0.001397817,0.004184266],"category_scores_gemma":[0.03075301,0.0004535317,0.000798335,0.003681476,0.000816812,0.002761759,0.003028533,0.002234032,0.001672392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005154794,"about_ca_system_score_gemma":0.01967057,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2241396,"about_ca_topic_score_gemma":0.323214,"domain_scores_codex":[0.9914743,0.003096075,0.0009207241,0.0007056102,0.003265125,0.0005382843],"domain_scores_gemma":[0.9655289,0.0110978,0.002611271,0.002675447,0.01571144,0.002374999],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002280368,0.0001439179,0.05449698,0.003763484,0.0002728355,0.0002000019,0.001340882,0.003423881,0.0021735,0.02794176,0.2581495,0.6478652],"study_design_scores_gemma":[0.00008931592,0.0002547771,0.04698889,0.004554252,0.0002016408,0.0003468815,0.001323429,0.008780246,0.00319117,0.02109429,0.912979,0.000196148],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0280408,0.09221905,0.3218057,0.2003303,0.01534532,0.003734503,0.08618239,0.009777411,0.2425646],"genre_scores_gemma":[0.2507269,0.1245694,0.4785086,0.03491492,0.007770742,0.002141009,0.07255124,0.0007901473,0.02802694],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7758604,"threshold_uncertainty_score":0.44567,"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."}}