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Record W4388894222 · doi:10.1126/scitranslmed.adg2773

Evidence for the contribution of the gut microbiome to obesity and its reversal

2023· review· en· W4388894222 on OpenAlexaff
Douwe F. de Wit, Nordin M.J. Hanssen, Koen Wortelboer, Hilde Herrema, Elena Rampanelli, Max Nieuwdorp

Bibliographic record

VenueScience Translational Medicine · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsMicrobiomeObesityGut microbiomeCausality (physics)ProbioticGut floraBiologyDysbiosisHuman obesityPandemicBioinformaticsMedicinePhysiologyImmunologyCoronavirus disease 2019 (COVID-19)DiseaseInternal medicineEndocrinologyGeneticsBacteria

Abstract

fetched live from OpenAlex

Obesity has become a worldwide pandemic affecting more than 650 million people and is associated with a high burden of morbidity. Alongside traditional risk factors for obesity, the gut microbiome has been identified as a potential factor in weight regulation. Although rodent studies suggest a link between the gut microbiome and body weight, human evidence for causality remains scarce. In this Review, we postulate that existing evidence remains to establish a contribution of the gut microbiome to the development of obesity in humans but that modified probiotic strains and supraphysiological dosages of microbial metabolites may be beneficial in combatting obesity.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.972
Threshold uncertainty score0.248

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.148
GPT teacher head0.433
Teacher spread0.285 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations39
Published2023
Admission routes1
Has abstractyes

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