{"id":"W3092404798","doi":"10.1139/gen-2020-0136","title":"Gut microbiome-mediated epigenetic regulation of brain disorder and application of machine learning for multi-omics data analysis","year":2020,"lang":"en","type":"review","venue":"Genome","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of Lethbridge; University of Calgary","funders":"","keywords":"Biology; Epigenetics; Gut flora; Disease; Microbiome; Bioinformatics; Omics; Dysbiosis; Computational biology; Neuroscience; Metabolomics; Gut–brain axis; Systems biology; Mechanism (biology); Immunology; Medicine; Genetics; Pathology; Gene","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002496236,0.0002018414,0.0008517005,0.000152798,0.00004425524,0.000006574686,0.0002916203,0.0002609407,0.000004275612],"category_scores_gemma":[0.00008364667,0.0001933922,0.0001796899,0.0003424585,0.00006047836,0.000001957311,0.0002306731,0.00008990401,0.000001669573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001357003,"about_ca_system_score_gemma":0.0001198012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004482582,"about_ca_topic_score_gemma":0.00009329348,"domain_scores_codex":[0.9986351,0.00008925749,0.0005589621,0.0005262334,0.00004316478,0.0001473561],"domain_scores_gemma":[0.9986827,0.00003566176,0.0006061234,0.0005547522,0.00006723621,0.00005347242],"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":[0.00003029624,0.00007701999,0.0001924102,0.01202246,0.001189371,1.144783e-7,0.00005318076,0.00009367541,0.7024199,0.000006834575,0.00002582702,0.2838889],"study_design_scores_gemma":[0.0003546723,0.0001042858,0.0009724674,0.00007698312,0.00131033,0.000002301469,0.000006349981,0.001870486,0.0001013908,0.000001511116,0.9950032,0.0001960189],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003532201,0.9212006,0.0751173,0.00003576195,0.00001478432,0.0008322343,0.002439679,0.000004688804,0.000001687891],"genre_scores_gemma":[0.001846992,0.9223151,0.005449644,0.00001895327,0.00005019363,0.0000268806,0.07017342,0.0000363825,0.0000825027],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9949774,"threshold_uncertainty_score":0.7886304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03333717208977121,"score_gpt":0.3312150843387467,"score_spread":0.2978779122489755,"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."}}