{"id":"W2338039188","doi":"10.1101/047142","title":"Detecting DNA Methylation using the Oxford Nanopore Technologies MinION sequencer","year":2016,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Ontario Institute for Cancer Research","funders":"","keywords":"Minion; Nanopore sequencing; Nanopore; DNA sequencer; 5-Methylcytosine; DNA methylation; DNA sequencing; DNA; Computational biology; Computer science; Biology; Genetics; Nanotechnology; Gene; Materials science","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004460603,0.0004452919,0.0003134021,0.0001016103,0.0003361456,0.00009700615,0.0005804136,0.000641736,0.000004220104],"category_scores_gemma":[0.0002624594,0.0003304933,0.0001651188,0.0001676538,0.000254306,0.000002659386,0.001010411,0.0003003207,0.000003701462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000955511,"about_ca_system_score_gemma":0.0001860165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001136947,"about_ca_topic_score_gemma":0.000004191375,"domain_scores_codex":[0.9980798,0.0001001749,0.0003835676,0.0008153415,0.0001912255,0.0004299429],"domain_scores_gemma":[0.998019,0.00003183239,0.0004259738,0.001160161,0.0003093107,0.00005370193],"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":[0.00001098145,0.00001383033,0.002653806,0.00005303949,0.0001639121,0.00000265943,0.000006185222,0.00006178556,0.9968821,0.00007481217,0.00004540544,0.00003148888],"study_design_scores_gemma":[0.0001879807,0.0000527001,0.004143622,0.0001154801,0.0000836658,5.152384e-8,0.00001795691,0.0001472703,0.9868287,0.00002770369,0.007892574,0.0005023167],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9879364,0.007193729,0.002987209,0.0003653684,0.0008209088,0.0004986959,0.0001111838,0.00007087099,0.00001559863],"genre_scores_gemma":[0.9949315,0.001152133,0.003180203,0.000062602,0.0004749527,0.0001101659,2.812386e-7,0.00008296406,0.000005218312],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01005342,"threshold_uncertainty_score":0.9999147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02066978874778371,"score_gpt":0.2389332110232731,"score_spread":0.2182634222754893,"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."}}