{"id":"W4401200522","doi":"10.1093/bioadv/vbae108","title":"Investigating alignment-free machine learning methods for HIV-1 subtype classification","year":2024,"lang":"en","type":"article","venue":"Bioinformatics Advances","topic":"HIV Research and Treatment","field":"Immunology and Microbiology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Canada Research Chairs","keywords":"Human immunodeficiency virus (HIV); Computer science; Artificial intelligence; Machine learning; Virology; Computational biology; Medicine; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000499069,0.0001329924,0.000154027,0.0001088196,0.000241135,0.00006495871,0.0001927334,0.00008214828,0.00009755916],"category_scores_gemma":[0.0005314002,0.0001006079,0.00006834175,0.0001388681,0.0001150565,0.000317036,0.00007257252,0.0001819246,0.0007416712],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000569335,"about_ca_system_score_gemma":0.00006894523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006274473,"about_ca_topic_score_gemma":0.000005399063,"domain_scores_codex":[0.9991229,0.00008905561,0.0003017299,0.0001442073,0.00004008387,0.0003020339],"domain_scores_gemma":[0.9991268,0.0005059824,0.00008475493,0.0002031588,0.00004426946,0.0000350463],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003857516,0.00005037305,0.001682112,0.0006464491,0.0003138462,0.000001188545,0.00174345,0.00006492704,0.04288044,0.01394633,0.007234257,0.931398],"study_design_scores_gemma":[0.0007688925,0.0002577937,0.0001599848,0.00008949241,0.00004254423,0.00001641663,0.0006686157,0.02654661,0.02162208,0.002522584,0.9471385,0.000166429],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01060468,0.145412,0.8100829,0.004506301,0.002460534,0.002337732,0.001175827,0.001100563,0.0223195],"genre_scores_gemma":[0.1339328,0.003342785,0.8451777,0.000198894,0.0001177881,0.0005447178,0.0050592,0.00006224723,0.01156392],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9399043,"threshold_uncertainty_score":0.953293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03916500014261359,"score_gpt":0.355114292073487,"score_spread":0.3159492919308735,"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."}}