{"id":"W4403791586","doi":"10.1101/2024.10.24.620090","title":"EpigeneticAgePipeline: an R package for comprehensive assessment of epigenetic age metrics from methylation microarrays","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Epigenetics; R package; Computational biology; Methylation; DNA methylation; DNA microarray; Computer science; Microarray; Biology; Bioinformatics; Genetics; Gene expression; Gene; Programming language","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":[0.005772409,0.003381944,0.002556467,0.002588843,0.0008242473,0.003181878,0.003276072,0.001026755,0.06236],"category_scores_gemma":[0.02157999,0.002179086,0.00299668,0.001875622,0.0006891632,0.001996625,0.002967609,0.003269288,0.04014113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006851739,"about_ca_system_score_gemma":0.003185319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003377678,"about_ca_topic_score_gemma":0.005090952,"domain_scores_codex":[0.9973787,0.0008050344,0.0002326262,0.0007906948,0.0005968062,0.0001960333],"domain_scores_gemma":[0.9940434,0.003700417,0.0005770398,0.0008166735,0.0006621456,0.0002002786],"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":[0.001148382,0.00009106093,0.01592045,0.00495868,0.00239608,0.0005190656,0.0005541033,0.01390378,0.01430594,0.01017538,0.8103192,0.1257079],"study_design_scores_gemma":[0.001097476,0.0004404363,0.02238451,0.0008149603,0.00162468,0.001280237,0.0002024824,0.1245953,0.04664631,0.04748461,0.7527745,0.0006544364],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.005311399,0.001315046,0.3843639,0.0005057181,0.0003968734,0.0003646913,0.1730637,0.431259,0.003419734],"genre_scores_gemma":[0.05090474,0.001289778,0.5431439,0.001474185,0.0002844231,0.004345863,0.1843134,0.206146,0.008097721],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.06236,"threshold_uncertainty_score":0.2086149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02894497248529982,"score_gpt":0.296981004098284,"score_spread":0.2680360316129842,"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."}}