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Record W1993504110 · doi:10.1126/science.1082358

Genetics and the Specificity of the Aging Process

2003· review· en· W1993504110 on OpenAlexaff
Siegfried Hekimi, Leonard Guarente

Bibliographic record

VenueScience · 2003
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsMcGill University
Fundersnot available
KeywordsMutantBiologyCaenorhabditis elegansLife spanModel organismGeneOrganismGeneticsLongevityEvolutionary biology

Abstract

fetched live from OpenAlex

The identification and study of long-lived mutant animals has provided valuable insights into the mechanisms that limit the life-span of organisms. Findings with the gene SIR2 suggest that the rate of aging can be regulated under certain conditions. Indeed, increased expression of SIR2 lengthens life-span by acting on biological processes that promote survival under conditions of scarcity. In addition, studies of mutant strains of Caenorhabditis elegans, in particular daf-2, clk-1, and isp-1 mutants, suggest that the biology of reactive oxygen species in the mitochondria and elsewhere might be the main determinant of life-span in this organism. Thus, the aging process may be more specific than previously anticipated on evolutionary grounds.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.003

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 head0.024
GPT teacher head0.305
Teacher spread0.280 · 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 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

Citations436
Published2003
Admission routes1
Has abstractyes

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