{"id":"W4206679078","doi":"10.1101/2022.01.04.21268588","title":"The epidemiological impact of the Canadian COVID Alert App","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"COVID-19 Digital Contact Tracing","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Case fatality rate; Quarantine; Demography; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Medicine; Pandemic; Transmission (telecommunications); 2019-20 coronavirus outbreak; Epidemiology; Geography; Environmental health; Virology; Population; Computer science; Outbreak; Infectious disease (medical specialty); Disease; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"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":[0.002937254,0.0008280543,0.0004536337,0.00136625,0.001602093,0.002168655,0.001261269,0.0005168535,0.002293073],"category_scores_gemma":[0.01291056,0.0002803475,0.0009977811,0.001196001,0.000966038,0.0008623621,0.0009161278,0.0008636642,0.0002072419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02916457,"about_ca_system_score_gemma":0.0318419,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9643224,"about_ca_topic_score_gemma":0.9724059,"domain_scores_codex":[0.996936,0.0005949857,0.0001075095,0.0003657635,0.001326926,0.0006687836],"domain_scores_gemma":[0.99168,0.002214457,0.001277602,0.0002892032,0.003914507,0.0006242959],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001582092,0.0003879795,0.8561791,0.001264964,0.0009483261,0.0005774235,0.00211428,0.03020316,0.005178132,0.003203111,0.006864701,0.09149683],"study_design_scores_gemma":[0.00006759512,0.001017511,0.946714,0.0002754938,0.0007730543,0.0003343871,0.003214692,0.03461832,0.002355353,0.0007062993,0.00981713,0.000106055],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9733467,0.00210829,0.00142636,0.001892675,0.00004700328,0.0002253858,0.004603017,0.0001064023,0.0162442],"genre_scores_gemma":[0.9957022,0.0007743749,0.001240941,0.0002139428,0.00001283056,0.00002349788,0.0008048794,0.0000107636,0.00121655],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03567755,"threshold_uncertainty_score":0.2116047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06301673846695792,"score_gpt":0.3339788744848487,"score_spread":0.2709621360178908,"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."}}