{"id":"W3184046291","doi":"10.1016/j.idm.2021.07.003","title":"On testing for infections during epidemics, with application to Covid-19 in Ontario, Canada","year":2021,"lang":"en","type":"article","venue":"Infectious Disease Modelling","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Agency of Canada; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo","keywords":"Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Public health; 2019-20 coronavirus outbreak; Coronavirus; Transmission (telecommunications); Environmental health; Estimation; Geography; Medicine; Virology; Statistics; Infectious disease (medical specialty); Outbreak; Pathology; Computer science; Mathematics; Disease","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":[0.0088471,0.001112605,0.001031519,0.001614941,0.001960327,0.001871902,0.002706389,0.001145675,0.004771779],"category_scores_gemma":[0.02372681,0.0006481156,0.001284777,0.002659735,0.002060328,0.0006978784,0.001510934,0.001165508,0.0003169445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0396422,"about_ca_system_score_gemma":0.04641355,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9933351,"about_ca_topic_score_gemma":0.9907307,"domain_scores_codex":[0.9967438,0.001712741,0.0001778732,0.0004302564,0.0004967689,0.0004385038],"domain_scores_gemma":[0.9895237,0.006737913,0.0009081846,0.0003414263,0.002023713,0.0004650936],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006865913,0.0001730692,0.3136753,0.0005455264,0.0005152969,0.001077913,0.002145673,0.529791,0.0005822115,0.05422217,0.02479666,0.07178863],"study_design_scores_gemma":[0.0003038748,0.0002546412,0.1277863,0.0003253069,0.0004092779,0.0002374475,0.001824516,0.8357024,0.0002808524,0.01204628,0.02069965,0.0001294203],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7427857,0.008476101,0.1286121,0.01825778,0.0003727836,0.002665883,0.04742585,0.001128139,0.05027574],"genre_scores_gemma":[0.9500332,0.002473443,0.02849715,0.0004618925,0.00005625759,0.0003672171,0.004003523,0.00006675258,0.01404048],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0396422,"threshold_uncertainty_score":0.2876256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04244327777541933,"score_gpt":0.2844728496814775,"score_spread":0.2420295719060581,"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."}}