{"id":"W3161162371","doi":"10.7490/f1000research.1117638.1","title":"Personalized and graph genomes reveal missing signal in epigenomic data","year":2019,"lang":"en","type":"article","venue":"Faculty of 1000 Research Ltd","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University and Génome Québec Innovation Centre; McGill University","funders":"","keywords":"Genome; Epigenomics; Reference genome; 1000 Genomes Project; Biology; Indel; Computational biology; Genetics; Human genome; Genomics; Gene; DNA methylation; 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":[],"consensus_categories":[],"category_scores_codex":[0.001571804,0.0001166866,0.0002285522,0.0001226547,0.00007766692,0.0000303168,0.0005297003,0.00009222994,0.00004372051],"category_scores_gemma":[0.0001113475,0.0001053032,0.00004466656,0.0001353436,0.0002532221,0.000001972213,0.0007754791,0.0001445042,0.00001427791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001648228,"about_ca_system_score_gemma":0.0001542082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001874411,"about_ca_topic_score_gemma":0.0000668768,"domain_scores_codex":[0.9984024,0.0001868362,0.0002409329,0.0005056522,0.0003107529,0.000353385],"domain_scores_gemma":[0.9990433,0.0000711599,0.00005378013,0.0005583647,0.0001905898,0.0000827614],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001230367,0.00003971503,0.07891316,0.00005577263,0.00006656324,0.000002583634,0.0002886821,0.00001644273,0.9098598,0.00004668041,0.002411385,0.008176197],"study_design_scores_gemma":[0.00453674,0.001272164,0.4207001,0.000146328,0.000029685,0.00002910518,0.002928372,0.0004499133,0.1369389,0.002658457,0.4294756,0.0008345923],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9893109,0.008268094,0.00001646923,0.0007433222,0.00002513549,0.0002413046,0.0003305704,0.000001072283,0.001063097],"genre_scores_gemma":[0.9947043,0.0009897201,0.0008391174,0.00002890378,0.00006340392,0.000005310105,0.000246558,0.00001485964,0.003107817],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7729208,"threshold_uncertainty_score":0.4294139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06028830714823331,"score_gpt":0.3542101262783046,"score_spread":0.2939218191300713,"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."}}