{"id":"W4393428930","doi":"10.5281/zenodo.8408392","title":"HG002 data for Profiling Chromatin Accessibility in Humans Using Adenine Methylation and Long-Read Sequencing","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"","keywords":"Profiling (computer programming); Computational biology; DNA methylation; Computer science; Methylation; Chromatin; Biology; Genetics; DNA; Operating system; Gene; Gene expression","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":[0.001167141,0.00206154,0.002004219,0.001838185,0.001065782,0.001850893,0.002897828,0.002256572,0.0445149],"category_scores_gemma":[0.003407195,0.0007171326,0.001196864,0.004333166,0.0004215506,0.0005492202,0.001584791,0.001416314,0.04175688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008659068,"about_ca_system_score_gemma":0.001671993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01452566,"about_ca_topic_score_gemma":0.03301136,"domain_scores_codex":[0.9989746,0.0001821956,0.00009404924,0.0003918811,0.0002356249,0.0001216053],"domain_scores_gemma":[0.9986529,0.0004508793,0.0001360979,0.000390122,0.0002207677,0.0001492775],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005998083,0.00007773304,0.004646366,0.002238506,0.0003315744,0.0002173662,0.00008952326,0.001267637,0.003706723,0.0009400914,0.9771729,0.008711813],"study_design_scores_gemma":[0.001027593,0.0001157927,0.02493065,0.000469524,0.000343652,0.0005735965,0.00009911874,0.0011137,0.005068978,0.003676227,0.9624857,0.0000953763],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0007042535,0.0001126192,0.0002966581,0.00002682359,0.00001216312,0.000008512922,0.9980195,0.0003727085,0.0004469139],"genre_scores_gemma":[0.0006838978,0.00003822321,0.0004276459,0.00003345982,0.000003271982,0.00004653869,0.9983449,0.00009141723,0.0003307522],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0445149,"threshold_uncertainty_score":0.1489171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1242479678191084,"score_gpt":0.3507965880583915,"score_spread":0.2265486202392832,"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."}}