{"id":"W4389357860","doi":"10.1101/2023.12.03.569831","title":"Identification and Analysis of SARS-CoV-2 Mutation and Subtype using 2x tiled Primer Set with Oxford Nanopore Technologies Sequencing for Enhanced Variant Detection and Surveillance in Seoul, Korea","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Peter's Hospital","funders":"","keywords":"Amplicon; Primer (cosmetics); Nanopore sequencing; Virology; DNA sequencing; Multiplex; Multiplex polymerase chain reaction; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Biology; Computational biology; Coronavirus; Sequence analysis; Mutation; Genotyping; Genotype; Coronavirus disease 2019 (COVID-19); Genetics; Polymerase chain reaction; Gene; Medicine; Infectious disease (medical specialty)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000618449,0.0003984299,0.000364462,0.000572391,0.0002578237,0.000424293,0.000249374,0.0004088164,0.0006758693],"category_scores_gemma":[0.000558764,0.0003510453,0.0005123426,0.0004112782,0.0001969982,0.0001885411,0.0003292538,0.000331798,0.0004617542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002107106,"about_ca_system_score_gemma":0.0003366547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001471427,"about_ca_topic_score_gemma":0.003844579,"domain_scores_codex":[0.9994949,0.00007264581,0.00005744423,0.0002161832,0.000109886,0.00004899914],"domain_scores_gemma":[0.9998083,0.000043099,0.00003478042,0.00002718733,0.00006237788,0.00002437184],"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":[0.0003077031,0.0000878514,0.04442812,0.0001626495,0.00008220843,0.0002835686,0.0004515954,0.001377026,0.9353663,0.0001983962,0.0004318733,0.01682271],"study_design_scores_gemma":[0.00006796801,0.0009550803,0.2142503,0.0001033125,0.0002750568,0.002372626,0.0009340821,0.04964959,0.7142836,0.0006738484,0.01634347,0.00009107084],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9511378,0.0009318069,0.04249772,0.0001060209,0.00005574981,0.0001826572,0.003460315,0.0002578041,0.001370121],"genre_scores_gemma":[0.8349033,0.0003913155,0.152273,0.0003127021,0.00001069248,0.0002941519,0.009020911,0.0001336884,0.002660243],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001471427,"threshold_uncertainty_score":0.003270686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04819078376011218,"score_gpt":0.3123187808920564,"score_spread":0.2641279971319443,"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."}}