{"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":"codex-gemma-dda1882f352a","candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.002504987,0.0002946031,0.0004104149,0.0001054021,0.000700953,0.0002842993,0.005998788,0.000171261,0.00006828374],"category_scores_gemma":[0.002934792,0.0001517641,0.0006523122,0.0004174128,0.000183596,0.00010658,0.004097485,0.001244263,0.00001408407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001293905,"about_ca_system_score_gemma":0.004169133,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1592685,"about_ca_topic_score_gemma":0.1586388,"domain_scores_codex":[0.997096,0.0006715845,0.0005033583,0.0006375413,0.0005054376,0.0005861001],"domain_scores_gemma":[0.9947729,0.002077144,0.0003479296,0.00239465,0.00008286399,0.0003244987],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002076031,0.00006055522,0.9020559,0.0001215909,0.0002883922,0.0001029058,0.00127424,0.02855448,0.0001047711,0.04921606,0.00631371,0.01188661],"study_design_scores_gemma":[0.0001254289,0.00009050795,0.9143258,0.00006401348,0.00001723779,0.00001783939,0.00001569058,0.01614457,0.00004493662,0.02035133,0.04840484,0.0003977887],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8942434,0.001879407,0.01918647,0.05271465,0.00550176,0.002362751,0.0002500194,0.0004755531,0.02338601],"genre_scores_gemma":[0.9976972,0.00002285321,0.0001890847,0.001640259,0.00006454773,0.00007093325,0.000004736675,0.00001387461,0.0002965324],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1034538,"threshold_uncertainty_score":0.9993792,"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."}}