{"id":"W3040384889","doi":"10.1016/j.cmet.2020.06.005","title":"A Universal Gut-Microbiome-Derived Signature Predicts Cirrhosis","year":2020,"lang":"en","type":"article","venue":"Cell Metabolism","topic":"Liver Disease Diagnosis and Treatment","field":"Medicine","cited_by":336,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia Hospital","funders":"National Center for Advancing Translational Sciences; National Institute of Environmental Health Sciences; Chiba University; University of California, San Diego; National Cancer Institute; National Institutes of Health; National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute; U.S. Department of Defense; University of Arizona Cancer Center; Fondation Leducq; U.S. Public Health Service; Howard Hughes Medical Institute","keywords":"Cirrhosis; Microbiome; Metagenomics; Gut microbiome; Biology; Computational biology; Medicine; Gastroenterology; Bioinformatics; Genetics; Gene","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":[0.0003342088,0.000319368,0.0005171697,0.0006461747,0.000270795,0.0007610901,0.0001596039,0.0004572697,0.002370058],"category_scores_gemma":[0.001437719,0.0001395577,0.0003349578,0.0007226911,0.0003155118,0.0003410425,0.0007386763,0.0005007182,0.000438951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00024285,"about_ca_system_score_gemma":0.0002312666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004553387,"about_ca_topic_score_gemma":0.0009120418,"domain_scores_codex":[0.9997281,0.00006572177,0.0000218511,0.00006875775,0.00004221053,0.00007336381],"domain_scores_gemma":[0.9992558,0.0001286922,0.0002926226,0.00006581788,0.0000792676,0.0001777666],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002556586,0.000096834,0.9082844,0.0001341653,0.0002945952,0.0004744242,0.00008022249,0.0003565389,0.05211017,0.0003118784,0.001274462,0.0340257],"study_design_scores_gemma":[0.00003396601,0.0003783779,0.9875635,0.0000440366,0.0001646875,0.001860238,0.0001542865,0.001413172,0.005772914,0.001007308,0.001587231,0.00002029221],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944021,0.001521827,0.0009288051,0.000291391,0.00004328914,0.00001267751,0.0009997293,0.00004779791,0.001752357],"genre_scores_gemma":[0.9981309,0.0002194948,0.000670634,0.0001150139,0.0000286735,0.000005779589,0.0006243078,0.00001210743,0.0001931046],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002370058,"threshold_uncertainty_score":0.00792861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01218734290194393,"score_gpt":0.2098971391217194,"score_spread":0.1977097962197755,"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."}}