{"id":"W2951983324","doi":"10.1038/s41598-019-45328-3","title":"A MiSeq-HyDRA platform for enhanced HIV drug resistance genotyping and surveillance","year":2019,"lang":"en","type":"article","venue":"Scientific Reports","topic":"HIV/AIDS drug development and treatment","field":"Medicine","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Public Health Agency of Canada","funders":"Rush University","keywords":"Sanger sequencing; HIV drug resistance; Genotyping; Drug resistance; Human immunodeficiency virus (HIV); Computational biology; Viral load; DNA sequencing; Medicine; Biology; Virology; Antiretroviral therapy; Microbiology; Genetics; Genotype; DNA; Gene","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":[],"consensus_categories":[],"category_scores_codex":[0.0008954755,0.000167096,0.0003195172,0.0001254096,0.0002232652,0.0001076553,0.00004986964,0.0000476805,0.00009462461],"category_scores_gemma":[0.0001009069,0.0001367526,0.00008117189,0.0002426487,0.00009743933,0.0001271083,0.00003841364,0.00006557814,0.00006642649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009058846,"about_ca_system_score_gemma":0.0002044991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001652682,"about_ca_topic_score_gemma":0.00006654501,"domain_scores_codex":[0.9981114,0.00000928107,0.0004071425,0.0007670817,0.0003537347,0.0003513937],"domain_scores_gemma":[0.9988363,0.00006622943,0.0001993972,0.0005891576,0.0001623731,0.000146552],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001260818,0.0006212401,0.2558654,0.002405839,0.0006433799,0.001287631,0.01283058,0.00001950603,0.2926962,0.001010572,0.4192156,0.01214325],"study_design_scores_gemma":[0.002689131,0.00002845673,0.009606746,0.000478989,0.00006732838,0.0002037888,0.0003518133,0.0001954799,0.1294171,0.00409213,0.8523134,0.0005556116],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9850637,0.0007315879,0.000337461,0.001476674,0.002021635,0.001304311,0.00000442917,0.00008318078,0.008977058],"genre_scores_gemma":[0.6424209,0.00001027853,0.003450732,0.0000309003,0.00003487284,0.00004939045,0.0001039789,0.00001565477,0.3538832],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4330978,"threshold_uncertainty_score":0.5576607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009423573163279873,"score_gpt":0.2393300175583436,"score_spread":0.2299064443950637,"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."}}