{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001155529,0.0007637984,0.0007551713,0.0007572463,0.000400069,0.0005939569,0.0008459431,0.0009088901,0.005573256],"category_scores_gemma":[0.001986095,0.0006688448,0.0004409069,0.0004635509,0.0002999221,0.000664631,0.0006570318,0.0009207586,0.002364408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004641518,"about_ca_system_score_gemma":0.0004552625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001755893,"about_ca_topic_score_gemma":0.003050842,"domain_scores_codex":[0.9993369,0.00007556896,0.00005595788,0.0002548044,0.0002279027,0.0000488408],"domain_scores_gemma":[0.9991251,0.0003588559,0.0001370584,0.0001454166,0.0001453413,0.00008829784],"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":[0.0002034918,0.00003137003,0.003774723,0.0002183844,0.00005202512,0.00006472347,0.0001078168,0.003149087,0.9606026,0.001123047,0.002387448,0.02828529],"study_design_scores_gemma":[0.0000210301,0.0001075983,0.01138044,0.00002603733,0.00004137163,0.0002996502,0.00003277494,0.1046478,0.8699529,0.001235113,0.01219389,0.00006138577],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3339101,0.001251685,0.6194536,0.0003140011,0.0001812733,0.0002225886,0.01774929,0.02072517,0.006192261],"genre_scores_gemma":[0.3212609,0.0004949611,0.652394,0.0002334798,0.00003125313,0.0004971884,0.01518276,0.001271647,0.008633802],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005573256,"threshold_uncertainty_score":0.01864433,"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."}}