{"id":"W2037909948","doi":"10.12688/f1000research.6037.2","title":"Long read nanopore sequencing for detection of HLA and CYP2D6 variants and haplotypes","year":2015,"lang":"en","type":"preprint","venue":"F1000Research","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":120,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"Hospital for Sick Children; Ontario Genomics; Ontario Genomics Institute; Genome Canada","keywords":"Haplotype; Biology; Minion; International HapMap Project; Genomics; Genetics; Nanopore sequencing; Population; Haplotype estimation; DNA sequencing; Genome; Computational biology; Genotype; Gene; Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005275026,0.0002528061,0.0002985405,0.000366768,0.0002562721,0.0003569354,0.000252185,0.0006627514,0.001683958],"category_scores_gemma":[0.001080537,0.0001909124,0.0002206638,0.0002966591,0.0002359978,0.0003085083,0.0003756425,0.000478758,0.0009903678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002722283,"about_ca_system_score_gemma":0.0002297905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008031127,"about_ca_topic_score_gemma":0.00304103,"domain_scores_codex":[0.9996868,0.00007242628,0.00002037078,0.0001015591,0.000096879,0.00002188306],"domain_scores_gemma":[0.9995736,0.0002131893,0.00005447985,0.00007484831,0.0000562177,0.0000275801],"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":[0.00007833917,0.00001222367,0.001921465,0.00008456924,0.00001796963,0.00006616642,0.000055623,0.0006043514,0.9788655,0.0004104165,0.0008239131,0.01705946],"study_design_scores_gemma":[0.0000254979,0.0002092054,0.05201044,0.00005798325,0.00004981513,0.0007689299,0.0001873029,0.02987398,0.8822811,0.003755298,0.03072605,0.00005441317],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5936716,0.00539654,0.3757367,0.001060147,0.000298374,0.0002457559,0.01285487,0.003115396,0.007620592],"genre_scores_gemma":[0.5864245,0.00184594,0.3954369,0.0008074999,0.00007306346,0.0003159665,0.008997133,0.0003617367,0.005737212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001683958,"threshold_uncertainty_score":0.005633354,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06465790169982544,"score_gpt":0.3155030929161274,"score_spread":0.250845191216302,"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."}}