{"id":"W3092826415","doi":"10.1101/2020.10.15.20212712","title":"A Multiplexed, Next Generation Sequencing Platform for High-Throughput Detection of SARS-CoV-2","year":2020,"lang":"en","type":"preprint","venue":"medRxiv","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; University of Toronto; Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital","funders":"Krembil Foundation; University of Toronto","keywords":"Population; Scalability; Contact tracing; Computer science; Turnaround time; Medicine; Coronavirus disease 2019 (COVID-19); Disease; Infectious disease (medical specialty); Environmental health; Pathology","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":[0.001672777,0.0008305063,0.0005879057,0.0007855757,0.0004061715,0.0009422236,0.0006004242,0.0007635713,0.002319395],"category_scores_gemma":[0.001639334,0.0004274499,0.0005204468,0.0003901593,0.0003579492,0.0005032435,0.0006907221,0.0009332556,0.001006558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005312273,"about_ca_system_score_gemma":0.0007202139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001256516,"about_ca_topic_score_gemma":0.002262447,"domain_scores_codex":[0.9985381,0.0002584698,0.00007268087,0.0006031228,0.0004516386,0.00007592666],"domain_scores_gemma":[0.9992521,0.0002202155,0.0001495204,0.00009365393,0.0001765091,0.0001079676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001800529,0.0004673426,0.01160435,0.0003478683,0.0002992867,0.0002893903,0.0001748576,0.00931051,0.9030273,0.0009133294,0.005573739,0.0661915],"study_design_scores_gemma":[0.000389867,0.004434145,0.03709941,0.0001134672,0.0003977477,0.001616177,0.0001250611,0.2129287,0.701905,0.002625548,0.03808762,0.0002772373],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5895132,0.005444717,0.3561459,0.001068183,0.0008987274,0.002403735,0.02989735,0.00900278,0.005625437],"genre_scores_gemma":[0.6335159,0.001251712,0.3414028,0.001665285,0.0002857913,0.001696372,0.01515181,0.0003468681,0.004683573],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002319395,"threshold_uncertainty_score":0.008846581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2541981935583544,"score_gpt":0.3448416509957549,"score_spread":0.09064345743740049,"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."}}