{"id":"W3196154994","doi":"10.1093/ofid/ofab382","title":"Tool for Estimating the Probability of Having COVID-19 With 1 or More Negative RT-PCR Results","year":2021,"lang":"en","type":"article","venue":"Open Forum Infectious Diseases","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research","funders":"Agencia Nacional de Investigación y Desarrollo","keywords":"Coronavirus disease 2019 (COVID-19); Medicine; Gold standard (test); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Reverse transcription polymerase chain reaction; 2019-20 coronavirus outbreak; Polymerase chain reaction; Coronavirus; Real-time polymerase chain reaction; Virology; Isolation (microbiology); Internal medicine; Infectious disease (medical specialty); Disease; Bioinformatics; Gene; Outbreak; Biology; Genetics; Gene expression","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0003385438,0.0001829828,0.0003681709,0.00004651179,0.0005266087,0.0001258244,0.0001450927,0.00004981388,0.00005374772],"category_scores_gemma":[0.01994262,0.0001115565,0.0001197122,0.0004651675,0.0001886427,0.0001636829,0.0001820315,0.0001352233,0.000002813676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001733423,"about_ca_system_score_gemma":0.001211258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005871463,"about_ca_topic_score_gemma":0.0008116091,"domain_scores_codex":[0.9985882,0.00009769784,0.0003989023,0.0004154035,0.0002237981,0.0002760095],"domain_scores_gemma":[0.99714,0.001520422,0.0002937934,0.0004832442,0.0004438522,0.0001186389],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.01396866,0.002959388,0.9113747,0.002936688,0.001025952,0.0003034598,0.004112321,0.004546035,0.007343138,0.00144198,0.007274293,0.04271333],"study_design_scores_gemma":[0.1153704,0.0170217,0.1975812,0.007265135,0.006451405,0.005755703,0.02814561,0.1510023,0.3989228,0.04633749,0.02210701,0.004039219],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9834443,0.00005469633,0.005835903,0.002813269,0.0001628044,0.003144276,0.0002262184,0.0001924195,0.00412615],"genre_scores_gemma":[0.9867015,6.371417e-7,0.008478721,0.004004792,0.00006764416,0.0004515482,0.00003241356,0.00003044162,0.0002322973],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7137936,"threshold_uncertainty_score":0.9883128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05794537015082847,"score_gpt":0.361925469917892,"score_spread":0.3039800997670635,"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."}}