{"id":"W4411798502","doi":"10.1101/2025.06.26.661849","title":"Simultaneous epigenomic profiling and regulatory activity measurement using e2MPRA","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Japan Society for the Promotion of Science; University of California, San Francisco; Ministry of Education, Culture, Sports, Science and Technology; Japan Agency for Medical Research and Development; Gladstone Institutes","keywords":"Profiling (computer programming); Epigenomics; Computer science; Computational biology; Chemistry; Biology; Programming language; DNA methylation; Gene expression; Biochemistry","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":[0.0005609526,0.0006395113,0.0003818847,0.0006577101,0.000177968,0.0006142767,0.0004159489,0.0004815944,0.001138877],"category_scores_gemma":[0.0002410245,0.0003233532,0.0003060869,0.0003303316,0.000332442,0.0004485184,0.0005665392,0.001054511,0.0006163403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002940553,"about_ca_system_score_gemma":0.0001918658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003138829,"about_ca_topic_score_gemma":0.000649156,"domain_scores_codex":[0.9994971,0.00007116815,0.00003012745,0.0001805776,0.0001613316,0.00005970591],"domain_scores_gemma":[0.9997258,0.00006432395,0.00007836182,0.00005731472,0.00003042664,0.00004378775],"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":[0.00002773495,0.00001739574,0.0002922673,0.00002004823,0.000005756427,0.00001705749,0.00000620795,0.00009786919,0.9967529,0.0001217779,0.00007477275,0.00256635],"study_design_scores_gemma":[0.000007784281,0.00005909131,0.00224663,0.000002696592,0.00001266764,0.0001354847,0.000007339225,0.002562228,0.9915433,0.00008955086,0.003325085,0.000008052294],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6381798,0.003298236,0.344676,0.0005878438,0.0001324069,0.0002610722,0.004548091,0.003216805,0.005099778],"genre_scores_gemma":[0.7762496,0.002507351,0.2027296,0.0004597049,0.00005787888,0.0004411513,0.005665325,0.0005305142,0.01135895],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001138877,"threshold_uncertainty_score":0.003809869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01376671700927186,"score_gpt":0.2205027248344393,"score_spread":0.2067360078251674,"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."}}