{"id":"W4281978976","doi":"10.3390/metabo12060512","title":"Network Approaches to Integrate Analyses of Genetics and Metabolomics Data with Applications to Fetal Programming Studies","year":2022,"lang":"en","type":"article","venue":"Metabolites","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"U.S. National Library of Medicine; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Diabetes and Digestive and Kidney Diseases; National Cancer Institute","keywords":"Metabolomics; Offspring; Computational biology; Computer science; Bayesian network; Omics; Disease; Bioinformatics; Biology; Machine learning; Medicine; Pregnancy; Genetics; Internal medicine","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":[0.005438112,0.001510902,0.000876144,0.003742552,0.0008687075,0.001917217,0.001832235,0.001194769,0.003976576],"category_scores_gemma":[0.02478517,0.001025448,0.001722967,0.003226685,0.00109831,0.00227381,0.003275913,0.002651111,0.0005548846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001552829,"about_ca_system_score_gemma":0.001427484,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009999451,"about_ca_topic_score_gemma":0.01280604,"domain_scores_codex":[0.9975247,0.001628322,0.000125356,0.0003749047,0.0002722454,0.00007452525],"domain_scores_gemma":[0.9848588,0.01199543,0.001204056,0.0009865729,0.0007002103,0.0002548868],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008455274,0.00008090238,0.008353258,0.0002856519,0.0006523546,0.0003542744,0.0003523456,0.6522611,0.003501525,0.2401394,0.001968205,0.09196633],"study_design_scores_gemma":[0.00001007372,0.00002736275,0.001509803,0.00004791987,0.00006157131,0.00008181125,0.0000488147,0.739706,0.0004542502,0.2537571,0.004268272,0.0000269467],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002237374,0.0001957625,0.9964324,0.000199723,0.00001945835,0.00002556737,0.0001986236,0.0001522647,0.0005387758],"genre_scores_gemma":[0.100058,0.001546901,0.8938276,0.0002380786,0.0001420548,0.0005247535,0.001009724,0.0003036562,0.002349158],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009999451,"threshold_uncertainty_score":0.02875984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1967839243104911,"score_gpt":0.3589558947657286,"score_spread":0.1621719704552375,"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."}}