{"id":"W2799888754","doi":"10.1161/circresaha.117.310909","title":"Personal Omics for Precision Health","year":2018,"lang":"en","type":"review","venue":"Circulation Research","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kellogg's (Canada)","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Diabetes and Digestive and Kidney Diseases","keywords":"Omics; Computational biology; Biology; Data science; Computer science; Medicine; Bioinformatics","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":[0.004683705,0.0011659,0.001506875,0.004426072,0.0006972575,0.003160791,0.001740357,0.003960861,0.01563626],"category_scores_gemma":[0.00730893,0.0004156172,0.001222206,0.003625635,0.002761308,0.004693574,0.00262138,0.006909113,0.007852616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002319427,"about_ca_system_score_gemma":0.003810734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001504384,"about_ca_topic_score_gemma":0.001662077,"domain_scores_codex":[0.9983725,0.0005110133,0.0001978348,0.0002704696,0.0005355276,0.0001126333],"domain_scores_gemma":[0.9939879,0.003792831,0.0003731749,0.0005390628,0.0009872777,0.0003197147],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000615418,0.00003964667,0.0002909343,0.007326096,0.0001575263,0.000280375,0.0001828426,0.0003911139,0.001004801,0.05625182,0.1165772,0.817436],"study_design_scores_gemma":[0.000005789185,0.00001416336,0.0002037192,0.001631862,0.00002367295,0.0004575648,0.00003662966,0.00004358692,0.0001564633,0.01285357,0.9845592,0.00001369147],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00008965555,0.9806432,0.002292925,0.008014017,0.002637056,0.00002144181,0.0001461544,0.00008035943,0.006075259],"genre_scores_gemma":[0.001493687,0.9835782,0.002261399,0.004843939,0.003862068,0.00004284633,0.0001866211,0.00003064777,0.003700635],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01563626,"threshold_uncertainty_score":0.0523085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.301322436119855,"score_gpt":0.5278792958247109,"score_spread":0.226556859704856,"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."}}