{"id":"W2955795503","doi":"10.1111/tan.13619","title":"Comparison of sequence‐specific oligonucleotide probe vs next generation sequencing for HLA‐A, B, C, DRB1, DRB3/B4/B5, DQA1, DQB1, DPA1, and DPB1 typing: Toward single‐pass high‐resolution HLA typing in support of solid organ and hematopoietic cell transplant programs","year":2019,"lang":"en","type":"article","venue":"HLA","topic":"Renal Transplantation Outcomes and Treatments","field":"Medicine","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"Calgary Laboratory Services; Alberta Children's Hospital","funders":"National Institutes of Health","keywords":"Genotyping; Typing; Human leukocyte antigen; Turnaround time; Sanger sequencing; Multilocus sequence typing; DNA sequencing; Biology; Polymerase chain reaction; Histocompatibility Testing; Computational biology; Genetics; Genotype; Computer science; Antigen; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007742368,0.0004708671,0.0006088261,0.001160532,0.0002291466,0.0009081681,0.0005409497,0.001146744,0.0005804031],"category_scores_gemma":[0.01238275,0.0003093238,0.0005752704,0.0007131528,0.0005704334,0.0008072644,0.0004742226,0.0005354671,0.0002557629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005429982,"about_ca_system_score_gemma":0.0004632856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001038614,"about_ca_topic_score_gemma":0.002017714,"domain_scores_codex":[0.9908932,0.00483336,0.0005493434,0.00102783,0.002465717,0.000230426],"domain_scores_gemma":[0.9914751,0.006074876,0.0005329738,0.0003924653,0.001362337,0.0001622915],"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":[0.005936893,0.0005387081,0.05727213,0.001012132,0.0005521994,0.0002704026,0.001170731,0.0113369,0.7850884,0.00123188,0.0004091468,0.1351805],"study_design_scores_gemma":[0.0002237337,0.01899398,0.186547,0.0001998062,0.00102889,0.002436135,0.0007921262,0.1062373,0.6742809,0.001203002,0.007884314,0.0001728587],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9396098,0.004827956,0.05259488,0.0002611436,0.0001571412,0.0001937568,0.0002876867,0.0002196346,0.001847961],"genre_scores_gemma":[0.8708175,0.001814324,0.1251675,0.0004973414,0.00005274249,0.0001481025,0.0007012543,0.00006639339,0.0007347224],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007742368,"threshold_uncertainty_score":0.04094601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1158709498254783,"score_gpt":0.3194079867495923,"score_spread":0.203537036924114,"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."}}