{"id":"W2993476941","doi":"10.1186/s40168-019-0767-6","title":"Advancing functional and translational microbiome research using meta-omics approaches","year":2019,"lang":"en","type":"review","venue":"Microbiome","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":338,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Ministero dello Sviluppo Economico; Ontario Ministry of Economic Development and Innovation; Government of Canada; Canadian Institutes of Health Research; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Genome Canada; Ontario Genomics; Ontario Genomics Institute; University of Ottawa","keywords":"Microbiome; Biology; Omics; Microbial ecology; Computational biology; Metagenomics; Medical microbiology; Translational research; Posttranslational modification; Bioinformatics; Proteomics; Data science; Biotechnology; Genetics; Microbiology; Bacteria; Computer science; Biochemistry","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0012123,0.0006077487,0.001493653,0.0005490925,0.0003207079,0.0001029649,0.0003356137,0.0008570871,0.00008736511],"category_scores_gemma":[0.00002092148,0.0005291066,0.0007041004,0.0004552743,0.0002923121,0.00001117324,0.0003015916,0.0006164851,0.0000851717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000976334,"about_ca_system_score_gemma":0.001070385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002359223,"about_ca_topic_score_gemma":0.00001648783,"domain_scores_codex":[0.9967306,0.0004078574,0.0007107328,0.001163914,0.000169974,0.000816925],"domain_scores_gemma":[0.998781,0.00007646997,0.0002529327,0.0005830972,0.0001464083,0.0001600509],"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":[0.00006054288,0.0002152367,0.00001047835,0.02581577,0.003741574,0.000007175506,0.0000782369,0.00002590522,0.8710415,0.0001286569,0.006762344,0.0921126],"study_design_scores_gemma":[0.0003168551,0.00006958641,0.000004984095,0.0005503333,0.001524099,0.0005349524,0.00001736743,0.000006203509,0.0009311661,0.00001243039,0.9954935,0.0005384963],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0005905182,0.9962723,0.000695268,0.00006196886,0.0003212085,0.001060885,0.0008813645,0.00001492482,0.000101606],"genre_scores_gemma":[0.00008227729,0.9866987,0.006018274,0.00008248823,0.000499184,0.00004909583,0.004671094,0.0001470417,0.001751803],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9887312,"threshold_uncertainty_score":0.999716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.435717386677676,"score_gpt":0.4214016577859939,"score_spread":0.01431572889168203,"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."}}