{"id":"W2165145892","doi":"10.1186/gm344","title":"Pharmacogene regulatory elements: from discovery to applications","year":2012,"lang":"en","type":"article","venue":"Genome Medicine","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of General Medical Sciences; Canadian Institutes of Health Research; Liver Center, University of California, San Francisco; University of California, San Francisco; National Institutes of Health","keywords":"Computational biology; Chromatin immunoprecipitation; Enhancer; Pharmacogenomics; Chromatin; DNA sequencing; Biology; Massive parallel sequencing; Genetics; Gene; Promoter; Transcription factor","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001705536,0.0001309788,0.0001297236,0.00003735612,0.00006320106,0.000007175589,0.0002049162,0.00005445008,0.0001491502],"category_scores_gemma":[0.00001299982,0.0001167937,0.00003618811,0.00008091228,0.00004543103,0.000004223965,0.0001305335,0.00004558331,0.00007562179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003023453,"about_ca_system_score_gemma":0.00002286208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001811473,"about_ca_topic_score_gemma":0.000006675154,"domain_scores_codex":[0.9991301,0.00001789105,0.0002267763,0.0002300785,0.0001217568,0.0002733808],"domain_scores_gemma":[0.999274,0.000005891023,0.00006505445,0.0004182338,0.00003382119,0.0002030391],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001361616,0.00004493712,0.002899103,0.000006389631,0.00005675305,2.599514e-7,0.00009749002,0.00002713952,0.9924628,0.000126155,0.001873156,0.002392188],"study_design_scores_gemma":[0.0009877365,0.000177346,0.04371089,0.00001176532,0.0000932518,0.000006822881,0.0002809252,0.00002681123,0.05112683,0.0001791548,0.9030511,0.0003473027],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9731236,0.003945377,0.02024722,0.000495414,0.0002461332,0.0003239017,0.000112211,0.00001180604,0.00149434],"genre_scores_gemma":[0.9910166,0.0002296886,0.002255925,0.001852327,0.002335403,0.0001016947,0.0009664641,0.00002695534,0.001214946],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.941336,"threshold_uncertainty_score":0.4762707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008180176494371352,"score_gpt":0.2579438825776704,"score_spread":0.2497637060832991,"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."}}