{"id":"W4212938086","doi":"10.21203/rs.3.rs-54086/v1","title":"Development and Validation of an Automated Emergency Department-Based Syndromic Surveillance System for Use at a Mass Gathering Event (2020 Arctic Winter Games, Yukon Canada) During a Global Pandemic: Implications for Lower Resourced and Remote Settings","year":2020,"lang":"en","type":"preprint","venue":"Research Square (Research Square)","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Agency of Canada","funders":"Public Health Agency; Public Health Agency of Canada","keywords":"Mass gathering; Arctic; Pandemic; Event (particle physics); The arctic; Emergency department; Meteorology; Coronavirus disease 2019 (COVID-19); Aeronautics; Climatology; Geography; History; Psychology; Oceanography; Engineering; Medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.00525331,0.000624985,0.001198631,0.0004498593,0.0007473344,0.0001980114,0.0006309917,0.0003674862,0.00002485018],"category_scores_gemma":[0.003665752,0.0006400291,0.0002265269,0.0008578518,0.000284924,0.0001669874,0.001292894,0.0009471619,0.000003358318],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005850523,"about_ca_system_score_gemma":0.004210617,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01171835,"about_ca_topic_score_gemma":0.03202172,"domain_scores_codex":[0.9910243,0.001405641,0.00141995,0.00210211,0.002340708,0.00170726],"domain_scores_gemma":[0.9923462,0.001277442,0.0004635974,0.001534109,0.003069593,0.001309029],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.02743055,0.001200022,0.6854842,0.1917736,0.003003258,0.0006707645,0.001970323,0.003204425,0.06230606,0.0001031439,0.01077342,0.01208023],"study_design_scores_gemma":[0.007236038,0.001369123,0.828337,0.009339139,0.0001518027,0.0001423906,0.001032104,0.1413449,0.004899921,0.0001532411,0.004758903,0.001235425],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9777547,0.0008044804,0.002094504,0.001405926,0.0001303911,0.009794949,0.007609189,0.0003936439,0.00001225077],"genre_scores_gemma":[0.9821097,0.0001774709,0.01044979,0.00001973911,0.0001212706,0.001770415,0.005118421,0.0001601547,0.00007300478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1824345,"threshold_uncertainty_score":0.9996051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06473486475459818,"score_gpt":0.3915228327489002,"score_spread":0.326787967994302,"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."}}