{"id":"W2966855909","doi":"10.1016/j.humimm.2019.07.235","title":"P182 Precision of next generation sequencing HLA genotyping for a national epitope matching program","year":2019,"lang":"en","type":"article","venue":"Human Immunology","topic":"Microbial infections and disease research","field":"Immunology and Microbiology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Genotyping; Matching (statistics); Human leukocyte antigen; Epitope; Computational biology; DNA sequencing; Genetics; Biology; Genotype; DNA; Mathematics; Antigen; Gene; Statistics","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":[0.0004229848,0.0001374497,0.0002643868,0.0002542302,0.0003276966,0.00003240111,0.0001841325,0.0002533853,0.001446551],"category_scores_gemma":[0.00007312079,0.0001343878,0.0001347615,0.0001265409,0.0001344071,0.0001617887,0.0001088065,0.0002230822,0.0001217314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001511359,"about_ca_system_score_gemma":0.0001949261,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001249518,"about_ca_topic_score_gemma":0.00004846084,"domain_scores_codex":[0.9987403,0.000173285,0.0003862146,0.0003092627,0.00004540009,0.0003455234],"domain_scores_gemma":[0.9991024,0.0001391313,0.0001570925,0.0002423662,0.0003450008,0.00001405139],"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":[0.00009087966,0.0001378721,0.0001372849,0.00005314165,0.0001587289,3.171482e-7,0.0002472193,0.00005808006,0.9763498,0.01197326,0.000721492,0.0100719],"study_design_scores_gemma":[0.005036501,0.00204379,0.003374207,0.0001840562,0.00007391645,0.0001477631,0.0006041176,0.0004487586,0.9043332,0.006406163,0.07670323,0.0006443167],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941159,0.002130574,0.000865115,0.00003581663,0.0005618876,0.00103986,0.00003800392,0.00007314097,0.00113972],"genre_scores_gemma":[0.9967663,0.00004923445,0.0007654563,0.00003958202,0.00007762279,0.0001547317,0.0005816411,0.00001629907,0.001549162],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07598174,"threshold_uncertainty_score":0.9994662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09578545828972086,"score_gpt":0.3460275737842426,"score_spread":0.2502421154945217,"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."}}