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Record W3190074802 · doi:10.1016/j.medmic.2021.100039

A transomic cohort as a reference point for promoting a healthy human gut microbiome

2021· article· en· W3190074802 on OpenAlexfundno aff
Zhuye Jie, Suisha Liang, Qiuxia Ding, Fei Li, Shanmei Tang, Dan Wang, Yuxiang Lin, Peishan Chen, Kaiye Cai, Xuemei Qiu, Qiang Li, Yunli Liao, Dongsheng Zhou, Heng Lian, Yong Zuo, Weiqiao Rao, Yan Ren, Yuan Wang, Jin Zi, Rong Wang, Hongcheng Zhou, Haorong Lu, Xiaohan Wang, Wei Zhang, Tao Zhang, Liang Xiao, Yang Zong, Weibin Liu, Huanming Yang, Jian Wang, Yong Hou, Xiao Liu, Karsten Kristiansen, Huanzi Zhong, Huijue Jia, Xun Xu

Bibliographic record

VenueMedicine in Microecology · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsMicrobiomeGut microbiomeMetagenomicsCohortBiobankBiologyHuman Microbiome ProjectCohort studyGut floraHuman microbiomeComputational biologyMedicineBioinformaticsImmunologyGeneticsInternal medicine

Abstract

fetched live from OpenAlex

More than a decade of gut microbiome studies have a common goal of improving human health. However, while most of the disease studies have focused on the elderly or the middle-aged, a reference cohort for the gut microbiome in young individuals has been lacking. It is also not clear what other omics data need to be measured to better understand the gut microbiome. Here, we present a cohort including 2183 adults with high-depth metagenomic shotgun sequencing data for the fecal microbiome and other omics data. In this multiomic cohort, we observe a number of vitamins, hormones, amino acids, and trace elements that correlated with the gut microbiome. Many of the associations are validated in an additional cohort consisting of 1404 individuals. Our comprehensive data are poised to provide advice to future populations and mechanistic study designs to better understand and manage our gut microbiome.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.334
Teacher spread0.318 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations42
Published2021
Admission routes1
Has abstractyes

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