{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003591515,0.001293133,0.001922224,0.007833669,0.0006466515,0.003505667,0.002920195,0.001977077,0.2090731],"category_scores_gemma":[0.0200464,0.0009750438,0.0008544176,0.01361872,0.0003280668,0.002252658,0.004296262,0.00197829,0.1011162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008442513,"about_ca_system_score_gemma":0.003695782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01155598,"about_ca_topic_score_gemma":0.01181911,"domain_scores_codex":[0.9988991,0.0002130326,0.0002014989,0.0001683853,0.0003906285,0.00012746],"domain_scores_gemma":[0.9906164,0.0037576,0.000626089,0.002399551,0.001170344,0.001429889],"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":[0.000311566,0.00005410551,0.00346988,0.001603241,0.0001288532,0.0001485162,0.0001674217,0.000780771,0.0007051532,0.004884664,0.9423014,0.04544452],"study_design_scores_gemma":[0.0001732172,0.00001642267,0.004384512,0.0003577252,0.00009162048,0.0001396149,0.00008473542,0.0006154943,0.0008977036,0.008882407,0.9843159,0.00004072697],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.0002949206,0.0003482218,0.002272766,0.0004826765,0.00007199857,0.00003759596,0.9879934,0.002839518,0.00565895],"genre_scores_gemma":[0.003468073,0.0008054139,0.003862594,0.0003250987,0.00005661887,0.0002588438,0.9865058,0.001113774,0.003603792],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.2090731,"threshold_uncertainty_score":0.6994191,"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."}}