{"id":"W4380876696","doi":"10.1038/s44222-023-00072-2","title":"Engineering the gut microbiome","year":2023,"lang":"en","type":"article","venue":"Nature Reviews Bioengineering","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":73,"is_retracted":false,"has_abstract":false,"ca_institutions":"Global Institute for Water Security; Concordia University; University of Saskatchewan","funders":"","keywords":"Microbiome; Dysbiosis; Human Microbiome Project; Gut microbiome; Biology; Computational biology; Gut flora; Fecal bacteriotherapy; Disease; Human microbiome; Metagenomics; Bioinformatics; Immunology; Medicine; Genetics; Gene; Antibiotics; Pathology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004406682,0.0001926623,0.0001937223,0.00008538482,0.00007532223,0.00002622312,0.000289392,0.0002584824,0.00001259479],"category_scores_gemma":[0.0001161699,0.0001344087,0.0001470644,0.0004841783,0.00001682371,0.000002949046,0.0001130138,0.0003660225,0.0002409153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001760727,"about_ca_system_score_gemma":0.000022638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001803476,"about_ca_topic_score_gemma":0.00000269925,"domain_scores_codex":[0.9990463,0.000023031,0.0002284212,0.0002697949,0.00006454025,0.0003679068],"domain_scores_gemma":[0.9994214,0.00001283433,0.0000449214,0.0004277693,0.00002591919,0.00006716274],"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":[0.00000187631,0.00000396347,0.00003719823,0.0001551502,0.0000173906,0.000002108427,0.00001689728,0.0002466844,0.9686559,0.0001003539,0.02837047,0.002391999],"study_design_scores_gemma":[0.00009723502,0.00001899132,0.00175965,0.00007509578,0.00001035132,0.00003180103,0.000005153512,0.0002561671,0.01499762,0.000001470794,0.9825746,0.0001719068],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.564168,0.4136091,0.005210749,0.005964518,0.005741753,0.003130161,0.0001154599,0.0008335451,0.001226736],"genre_scores_gemma":[0.9209328,0.06717744,0.003654088,0.002032269,0.002260151,0.0001528939,0.000548048,0.000171626,0.003070659],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9542041,"threshold_uncertainty_score":0.5481026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0091709245836775,"score_gpt":0.269636070762264,"score_spread":0.2604651461785865,"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."}}