{"id":"W3049021040","doi":"10.3390/v12080895","title":"A Comparison of Whole Genome Sequencing of SARS-CoV-2 Using Amplicon-Based Sequencing, Random Hexamers, and Bait Capture","year":2020,"lang":"en","type":"article","venue":"Viruses","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":123,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; University of Manitoba; Public Health Agency of Canada; University of Toronto; University Health Network; Dalhousie University; Health Sciences Centre; Sunnybrook Health Science Centre; Perimeter Institute; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; University of Toronto","keywords":"Amplicon; Genome; Biology; Multiplex; Multiple displacement amplification; Computational biology; DNA sequencing; Polymerase chain reaction; Genetics; Virology; Gene; DNA extraction","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":[0.001224493,0.0005812612,0.0006137102,0.0006965755,0.000287636,0.0006668018,0.000329962,0.0006939327,0.0007611974],"category_scores_gemma":[0.002136586,0.0004474696,0.0006877912,0.0005454609,0.0003222699,0.0004878232,0.0005274761,0.0004210432,0.0004429426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000387434,"about_ca_system_score_gemma":0.0003522396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009858551,"about_ca_topic_score_gemma":0.00273931,"domain_scores_codex":[0.9983758,0.0003393873,0.0001373788,0.0004725981,0.0005583205,0.0001165662],"domain_scores_gemma":[0.9991544,0.0003040193,0.00009352464,0.00009303163,0.000287542,0.00006747901],"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":[0.000740823,0.00008465238,0.003182613,0.0002778688,0.0001001716,0.00004456087,0.0001742391,0.001336125,0.981077,0.0001432301,0.0002776926,0.01256094],"study_design_scores_gemma":[0.00005542759,0.002166612,0.0748345,0.00005400597,0.0002446061,0.0007981546,0.0002585677,0.01557882,0.897782,0.0002309109,0.007919763,0.00007656948],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9721428,0.001669694,0.02050691,0.0001061377,0.00004802016,0.0001117285,0.00226099,0.0004374589,0.002716315],"genre_scores_gemma":[0.8641193,0.002247439,0.1055311,0.0004226619,0.00003582034,0.0003865966,0.02301393,0.0005210661,0.003722128],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001224493,"threshold_uncertainty_score":0.006475806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2025658069773117,"score_gpt":0.4022353769418807,"score_spread":0.199669569964569,"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."}}