{"id":"W3025512529","doi":"10.1101/2020.05.12.092387","title":"Comparison of SARS-CoV-2 Indirect and Direct Detection Methods","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Muscular Dystrophy Canada; University of Toronto; Toronto General Hospital; University Health Network; Sinai Health System; Lunenfeld-Tanenbaum Research Institute","funders":"Canadian Institutes of Health Research; Krembil Foundation","keywords":"RNA extraction; RNA; RNase P; Isolation (microbiology); Virology; TaqMan; Economic shortage; Biology; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Coronavirus disease 2019 (COVID-19); Computational biology; Real-time polymerase chain reaction; Medicine; Bioinformatics; Gene; Infectious disease (medical specialty); Genetics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0110292,0.002610253,0.001740925,0.002975965,0.0005641919,0.002185968,0.001959374,0.001800869,0.005708018],"category_scores_gemma":[0.01244476,0.001459231,0.001731273,0.001269929,0.001009421,0.00104133,0.002177344,0.001963678,0.004807007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008467206,"about_ca_system_score_gemma":0.0008084475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001014075,"about_ca_topic_score_gemma":0.00221356,"domain_scores_codex":[0.9766098,0.007497029,0.001316597,0.003476299,0.01026568,0.0008346094],"domain_scores_gemma":[0.989856,0.004403104,0.000979548,0.0007786376,0.003667948,0.0003148189],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.002604699,0.0005585898,0.03170463,0.006544743,0.0009975748,0.0001445344,0.001004018,0.002110942,0.8367905,0.001201186,0.003351319,0.1129873],"study_design_scores_gemma":[0.0001051675,0.003493513,0.02767812,0.000583934,0.001065975,0.0009973911,0.0003669492,0.006683108,0.9346849,0.0005864028,0.02348993,0.0002646293],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.533825,0.04171063,0.3746249,0.0009261906,0.00189101,0.004105504,0.01129672,0.003028921,0.02859108],"genre_scores_gemma":[0.4898873,0.01353604,0.4439121,0.001302489,0.0005550463,0.004563125,0.01871384,0.001096593,0.0264336],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0110292,"threshold_uncertainty_score":0.05832869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0893473137130839,"score_gpt":0.3590111967138742,"score_spread":0.2696638830007903,"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."}}