{"id":"W2031102033","doi":"10.1371/journal.pone.0097282","title":"HLA Diversity in the 1000 Genomes Dataset","year":2014,"lang":"en","type":"article","venue":"PLoS ONE","topic":"T-cell and B-cell Immunology","field":"Immunology and Microbiology","cited_by":209,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Heart Institute","funders":"National Institute of Allergy and Infectious Diseases; Office of Naval Research; National Institute of Neurological Disorders and Stroke; Race to Erase MS","keywords":"Biology; Genome; Genetics; 1000 Genomes Project; Identity by descent; Haplotype; Major histocompatibility complex; Human leukocyte antigen; Linkage disequilibrium; Reference genome; Sanger sequencing; Genomics; Evolutionary biology; DNA sequencing; Computational biology; Allele; Gene; Genotype; Single-nucleotide polymorphism","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003031875,0.0001046014,0.0002012903,0.00005906237,0.0002528045,0.000008356201,0.0005216357,0.0001501923,0.000834107],"category_scores_gemma":[0.00003085915,0.00007471405,0.00002944623,0.00008322498,0.0001910275,0.0000503459,0.0003608637,0.0003023028,0.002724891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001451743,"about_ca_system_score_gemma":0.00001048349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002449977,"about_ca_topic_score_gemma":0.0001164773,"domain_scores_codex":[0.9990479,0.0003091377,0.0001326667,0.0002000057,0.00003469955,0.0002755564],"domain_scores_gemma":[0.9993258,0.0001834455,0.00004734872,0.0004187204,0.0000165568,0.000008172565],"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":[0.00006711105,0.00130668,0.01563213,0.0000162223,0.0001993418,0.000005698605,0.0007786874,4.589846e-7,0.9678759,0.0008320662,0.01241158,0.0008741055],"study_design_scores_gemma":[0.004469738,0.0007505164,0.02702774,0.0000626472,0.0003806259,0.00004374973,0.0008364905,0.00001253344,0.4933881,0.001219473,0.4711944,0.0006140741],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930219,0.001476426,0.000004965813,0.00104665,0.0001055873,0.0001533077,0.0002092691,0.00003328283,0.003948611],"genre_scores_gemma":[0.996036,0.0001662437,0.00002862758,0.0008937898,0.00002942571,0.000008463262,0.001069525,0.000005544875,0.001762369],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4744879,"threshold_uncertainty_score":0.9980516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0384532121095314,"score_gpt":0.2111866681345919,"score_spread":0.1727334560250605,"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."}}