{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004948038,0.0005561793,0.0003765952,0.001353358,0.0009862178,0.001474473,0.001029994,0.0005491595,0.000968463],"category_scores_gemma":[0.009576651,0.0002450538,0.0004069356,0.0006726002,0.0004925622,0.0006404363,0.0007302371,0.0003032835,0.0006411304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00376736,"about_ca_system_score_gemma":0.007526824,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2433,"about_ca_topic_score_gemma":0.2073103,"domain_scores_codex":[0.9978343,0.0006251851,0.0003983081,0.0005514383,0.0004642779,0.0001264367],"domain_scores_gemma":[0.9899165,0.001885649,0.0005556707,0.0005806999,0.006750282,0.0003112269],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003062865,0.002099515,0.4619941,0.001495575,0.0005592706,0.001916195,0.007038299,0.03283031,0.1174801,0.001272025,0.0249388,0.345313],"study_design_scores_gemma":[0.000606225,0.001899366,0.4805609,0.0004733203,0.0004644692,0.000718119,0.005589306,0.4125151,0.07249083,0.0005827352,0.02384481,0.0002547694],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9260825,0.0001309953,0.04720939,0.0004827229,0.00008790158,0.004592097,0.009528246,0.008108406,0.003777765],"genre_scores_gemma":[0.8545101,0.000106891,0.1281261,0.0002484425,0.00002206104,0.001388897,0.01337897,0.0001552076,0.002063291],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7567,"threshold_uncertainty_score":0.4837676,"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."}}