MétaCan
Menu
Back to cohort
Record W3215146738 · doi:10.3390/diseases9040087

Ageing and Obesity Shared Patterns: From Molecular Pathogenesis to Epigenetics

2021· article· en· W3215146738 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.

Bibliographic record

VenueDiseases · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsEpigeneticsAgeingObesityDNA methylationManagement of obesityBioinformaticsMedicineBiologyGerontologyGeneticsWeight lossGeneGene expressionEndocrinology

Abstract

fetched live from OpenAlex

In modern societies, ageing and obesity represent medical challenges for healthcare professionals and caregivers. Obesity and ageing share common features including the related cellular and molecular pathways as well as the impacts they have as risk factors for a variety of diseases and health problems. Both of these health problems also share exercise and a healthy lifestyle as the best therapeutic options. Importantly, ageing and obesity also have common epigenetic changes (histone modification, DNA methylation, noncoding RNAs, and chromatin remodeling) that are also impacted by exercise. This suggests that epigenetic pathways are among the mechanisms via which exercise induces its benefits, including ageing and obesity improvements. Exploring these interrelations and based on the fact that both ageing and obesity represent risk factors for each other, would lead to optimizing the available therapeutic approaches towards improved obesity management and healthy ageing.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.294
Threshold uncertainty score0.572

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.008
GPT teacher head0.241
Teacher spread0.233 · 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