{"id":"W4387460903","doi":"10.1101/2023.10.05.561129","title":"Profiling Chromatin Accessibility in Humans Using Adenine Methylation and Long-Read Sequencing","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"RNA modifications and cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; University of British Columbia","funders":"Canada's Michael Smith Genome Sciences Centre","keywords":"Chromatin; Nanopore sequencing; DNA methylation; Computational biology; Biology; CpG site; DNA sequencing; DNA; Profiling (computer programming); Genome; Genetics; Epigenomics; Nanopore; Gene; Computer science; Nanotechnology; Gene expression","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":[0.0004971742,0.0002580891,0.0002392622,0.0003892262,0.0001497096,0.0003165124,0.0001906404,0.0005463679,0.00156671],"category_scores_gemma":[0.0004765849,0.0001830874,0.0002342162,0.0002214884,0.0002151272,0.0001422393,0.0002450606,0.0004405022,0.0005487023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001597368,"about_ca_system_score_gemma":0.0001032408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000477026,"about_ca_topic_score_gemma":0.0009906453,"domain_scores_codex":[0.9996835,0.00006759424,0.00001419805,0.0001205392,0.00009090301,0.00002325643],"domain_scores_gemma":[0.9997192,0.00009416944,0.00006542451,0.00004781523,0.000038426,0.00003499264],"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":[0.000139766,0.00001738476,0.004706607,0.00004398078,0.00004834888,0.0001087394,0.0000481647,0.000588152,0.9830756,0.0003066732,0.0002276521,0.01068886],"study_design_scores_gemma":[0.00001329247,0.0003127353,0.04216556,0.00001566109,0.00005527055,0.001415176,0.0000431407,0.005459954,0.9400413,0.0008949868,0.009553087,0.00002975839],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8722847,0.003402886,0.1153555,0.0003763325,0.00008291927,0.00005957842,0.003736957,0.001550633,0.003150507],"genre_scores_gemma":[0.9166136,0.0008709583,0.07621284,0.0002513062,0.00003556732,0.00004786407,0.002431171,0.000120445,0.003416261],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00156671,"threshold_uncertainty_score":0.005241156,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04452401746134532,"score_gpt":0.2934885022864877,"score_spread":0.2489644848251424,"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."}}