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Record W2948856752 · doi:10.1002/bies.201800257

The Microbiome Mediates Environmental Effects on Aging

2019· review· en· W2948856752 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBioEssays · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsCanada's Michael Smith Genome Sciences CentreUniversity of British ColumbiaCanadian Institute for Advanced Research
FundersCanadian Institutes of Health ResearchDeutsche Forschungsgemeinschaft
KeywordsLongevityMicrobiomeBiologyStressorDysbiosisEvolutionary biologyBioinformaticsGeneticsNeuroscience

Abstract

fetched live from OpenAlex

Humans' indigenous microbes strongly influence organ functions in an age- and diet-dependent manner, adding an important dimension to aging biology that remains poorly understood. Although age-related differences in the gut microbiota composition correlate with age-related loss of organ function and diseases, including inflammation and frailty, variation exists among the elderly, especially centenarians and people living in areas of extreme longevity. Studies using short-lived as well as nonsenescent model organisms provide surprising functional insights into factors affecting aging and implicate attenuating effects of microbes as well as a crucial role for certain transcription factors like forkhead box O. The unexpected beneficial effects of microbes on aged animals imply an even more complex interplay between the gut microbiome and the host. The microbiome constitutes the major interface between humans and the environment, is influenced by biosocial stressors and behaviors, and mediates effects on health and aging processes, while being moderated by sex and developmental stages.

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.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.979
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.019
GPT teacher head0.300
Teacher spread0.282 · 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