{"id":"W4310707155","doi":"10.1038/s41467-022-35017-7","title":"Genetically personalised organ-specific metabolic models in health and disease","year":2022,"lang":"en","type":"article","venue":"Nature Communications","topic":"Microbial Metabolic Engineering and Bioproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; Canadian Institutes of Health Research; Chief Scientist Office, Scottish Government Health and Social Care Directorate; NIHR Cambridge Biomedical Research Centre; Economic and Social Research Council; European Commission; NIHR BioResource; University of Cambridge; Department of Health and Social Care; Health and Social Care Research and Development Division; National Institute for Health and Care Research; Public Health Agency; Government of Canada; Science and Technology Facilities Council; Scottish Government; British Heart Foundation; European Federation of Pharmaceutical Industries and Associations; Dell EMC; Medical Research Council; Scottish Government Health and Social Care Directorate; Wellcome Trust; Research Councils UK; NHS Blood and Transplant","keywords":"Disease; Computational biology; Medicine; Bioinformatics; Biology; Pathology","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":[0.0002126933,0.00007916081,0.00009221092,0.00006109865,0.0002002467,0.00001188134,0.0003216241,0.00005231758,0.00000936793],"category_scores_gemma":[0.00005413659,0.0000846768,0.00002940564,0.000190715,0.00004996917,0.000002865566,0.000315278,0.0003691243,5.985991e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000152712,"about_ca_system_score_gemma":0.0001059826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000122124,"about_ca_topic_score_gemma":0.00002161754,"domain_scores_codex":[0.9993069,0.0001454273,0.0001375235,0.0002068695,0.00007865481,0.0001245859],"domain_scores_gemma":[0.9990644,0.000004669991,0.00003640053,0.000742871,0.00003209606,0.0001195045],"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":[0.000221027,0.0007038164,0.00238398,0.00005841555,0.00008068286,0.000001776504,0.001113511,0.006145361,0.858207,0.09427278,0.02107798,0.01573372],"study_design_scores_gemma":[0.0003836297,0.00004665492,0.004437679,0.000005916539,0.000007057298,0.00001335593,0.0001618793,0.001177773,0.0008877352,0.0003381676,0.992368,0.0001721719],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.4774724,0.5019028,0.0007631585,0.0187288,0.0002622458,0.0004425759,0.0001439669,0.00003907934,0.0002449679],"genre_scores_gemma":[0.9805574,0.01441562,0.00354475,0.0008812496,0.00006776743,0.00004996618,0.0003271211,0.00001383963,0.0001422219],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.97129,"threshold_uncertainty_score":0.345302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01447524130138335,"score_gpt":0.2595902561442451,"score_spread":0.2451150148428618,"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."}}