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Record W4243516397 · doi:10.1007/s11357-006-9011-y

Interventions in Aging and Age-Related Diseases: The Present and the Future

2006· article· en· W4243516397 on OpenAlexaff
Matt Kaeberlein, Simon Judge, Serap Mungan Ay, Jang Ym, Bhy Chung, Kim Jh, Kwak Hb, Speakman Jr, Roger P. Farrar, Ed Merritt, Anne Jennings, David W. Hammers, Martin L. Adamo, Wayne Mathey, James Walters

Bibliographic record

VenueAGE · 2006
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsMcGill University
FundersBiotechnology and Biological Sciences Research CouncilNational Institutes of HealthWellcome Trust
KeywordsPsychological interventionGerontologyPsychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

We are using two model organisms, the budding yeast, Saccharomyces cerevisiae, and the nematode, Caenorhabditis elegans, to identify evolutionarily conserved determinants of longevity and to characterize the genetic factors involved in life span extension from calorie restriction. Through genome-wide studies of longevity in yeast, we have determined that calorie restriction slows aging by down-regulation of the TOR, PKA, and Sch9 (Akt) nutrient-responsive kinases, and we are testing the degree to which this mechanism is conserved in C. elegans. In addition, we are performing a systematic analysis of the aging properties of ortholog pairs, in which one ortholog is known to regulate longevity in either yeast or C. elegans. Thus far, our analysis suggests a significant enrichment of longevity-determining genes among ortholog pairs, providing quantitative evidence that genetic pathways influencing aging are evolutionarily conserved. Future efforts will be aimed at testing candidate conserved longevity determinants in mice and monitoring life span and other phenotypes associated with aging in these animals.

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)0.007
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.005
Open science0.0010.001
Research integrity0.0050.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.020
GPT teacher head0.328
Teacher spread0.308 · 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 designTheoretical or conceptual
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

Citations1
Published2006
Admission routes1
Has abstractyes

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