{"id":"W2553822231","doi":"10.1016/j.cels.2016.10.019","title":"The International Human Epigenome Consortium Data Portal","year":2016,"lang":"en","type":"article","venue":"Cell Systems","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":198,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Centre Hospitalier Universitaire de Sherbrooke; McGill University Health Centre; Université de Sherbrooke; McGill University and Génome Québec Innovation Centre","funders":"Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke; McGill University; Canarie; Compute Canada; Canadian Institutes of Health Research; Genome Canada","keywords":"Epigenome; Epigenomics; Computer science; Data integration; Data sharing; Blueprint; Visualization; ENCODE; Download; Computational biology; Biology; World Wide Web; Database; DNA methylation; Data mining; Genetics; Gene","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0003835814,0.00007606439,0.00006069463,0.00001243905,0.0001233788,0.00005568582,0.0005463153,0.00006519659,0.00001872552],"category_scores_gemma":[0.0000424383,0.0000439473,0.00002787029,0.00001824577,0.00005617557,0.000003309694,0.0002112812,0.0000252585,0.00003939291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008311012,"about_ca_system_score_gemma":0.00003339941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002492253,"about_ca_topic_score_gemma":0.00003539171,"domain_scores_codex":[0.9992296,0.00004056737,0.0002066746,0.0002546209,0.0001288965,0.0001396874],"domain_scores_gemma":[0.9990692,0.00002185535,0.0001066641,0.000691711,0.00006429702,0.00004631759],"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":[0.000005710579,0.00001302499,0.00565151,0.000003967585,0.00002373341,0.00000150663,0.000005573187,0.000004555932,0.9891813,0.000363831,0.003717501,0.001027744],"study_design_scores_gemma":[0.0003036053,0.00005258697,0.001839908,0.000008666914,0.000007675778,0.000002163574,0.00004905645,0.00003293987,0.1685184,0.00006538912,0.8289988,0.0001207814],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9495132,0.007265973,0.0037398,0.0003158972,0.002066705,0.0002536783,0.000137713,0.00001578168,0.03669124],"genre_scores_gemma":[0.9869836,0.0004351541,0.00001867437,0.00001420265,0.0006173454,0.0000103056,0.0002221699,0.00001272686,0.01168581],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8252813,"threshold_uncertainty_score":0.1792119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0275696721970208,"score_gpt":0.27398725109855,"score_spread":0.2464175789015292,"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."}}