{"id":"W2790028253","doi":"10.1101/251967","title":"A multi-omic atlas of the human frontal cortex for aging and Alzheimer's disease research","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Institutes of Health","keywords":"Dementia; Dorsolateral prefrontal cortex; Histone; Biology; Neuroscience; Cognitive decline; Biomarker; Disease; Alzheimer's disease; Prefrontal cortex; Computational biology; Genetics; Bioinformatics; Cognition; Medicine; Gene; Internal medicine","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":[0.0007946041,0.0003050846,0.00029499,0.0000797275,0.0003186588,0.00009397558,0.0006045176,0.0003834898,0.000005269851],"category_scores_gemma":[0.00009142186,0.0002650805,0.0001731281,0.0000974061,0.0004732133,0.000005460651,0.001256496,0.0003861001,0.000003152694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003726445,"about_ca_system_score_gemma":0.0004039996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000367412,"about_ca_topic_score_gemma":0.00001237892,"domain_scores_codex":[0.9982231,0.00009921202,0.0004146245,0.0006052955,0.0002084726,0.0004492717],"domain_scores_gemma":[0.9978746,0.0000236888,0.0003019894,0.001153957,0.0004394335,0.0002064028],"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":[0.00008047741,0.0001061654,0.009787213,0.0003569319,0.0003613709,0.000001869276,0.00001923712,0.00002315181,0.985728,0.0002126928,0.00331635,0.000006585824],"study_design_scores_gemma":[0.002861337,0.0003358788,0.4241879,0.0009555128,0.0006129438,5.482347e-8,0.00002230095,0.007822303,0.5378776,0.00005289932,0.02373041,0.001540928],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9923487,0.004022647,0.00126181,0.0001208452,0.000532307,0.001196977,0.0004914667,0.00001887931,0.000006419744],"genre_scores_gemma":[0.9958014,0.0001648187,0.003067754,0.00009485098,0.0006433108,0.0001427022,0.000003160352,0.00007009162,0.00001187507],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4478504,"threshold_uncertainty_score":0.9999802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02889487906391069,"score_gpt":0.2824246856252094,"score_spread":0.2535298065612987,"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."}}