{"id":"W2950493549","doi":"10.1093/nar/gky677","title":"Umap and Bismap: quantifying genome and methylome mappability","year":2018,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":153,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Vector Institute; Princess Margaret Cancer Centre; University of Toronto","funders":"National Human Genome Research Institute; University Health Network; University of Toronto; Canadian Cancer Society; Princess Margaret Cancer Foundation; Natural Sciences and Engineering Research Council of Canada","keywords":"Biology; Genome; Genetics; Computational biology; DNA sequencing; Hybrid genome assembly; Cancer genome sequencing; Bisulfite sequencing; Whole genome sequencing; Genomics; Human genome; Reference genome; DNA methylation; Gene","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":[0.001785151,0.000111071,0.0001228537,0.0001057334,0.0003002342,0.00008173108,0.0001509369,0.0001741639,0.00005356474],"category_scores_gemma":[0.0003390275,0.000103218,0.00002729958,0.0001718174,0.0006265009,0.000005746796,0.0003928054,0.0001756417,0.00002515962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001507262,"about_ca_system_score_gemma":0.00004641063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004406246,"about_ca_topic_score_gemma":0.00004130703,"domain_scores_codex":[0.9984895,0.0002269947,0.00017588,0.0004822841,0.0002630749,0.0003622493],"domain_scores_gemma":[0.9991054,0.00005142779,0.0000290243,0.0003884529,0.0002705476,0.0001551725],"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":[0.00004238712,0.00002213161,0.01729511,0.00002639851,0.00001999719,0.000001081402,0.0001770617,3.634132e-7,0.9706633,0.0002346322,0.00005357518,0.01146395],"study_design_scores_gemma":[0.0007423877,0.001374022,0.3246192,0.0000135563,0.00001197526,0.00000608987,0.0003642307,0.0002535946,0.5414582,0.004137402,0.1266759,0.0003434293],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929186,0.003425085,0.0007083195,0.0003060018,0.00004770749,0.0002002868,0.000009143826,0.0000100874,0.002374799],"genre_scores_gemma":[0.9965052,0.000881505,0.001853323,0.00004158655,0.0003008656,0.00001196147,0.00001583898,0.00002210081,0.0003675986],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4292051,"threshold_uncertainty_score":0.4209109,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09086617335044819,"score_gpt":0.3920124527857351,"score_spread":0.3011462794352869,"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."}}