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Record W2112855370 · doi:10.1093/gerona/glp055

Familial Aggregation of Survival and Late Female Reproduction

2009· article· en· W2112855370 on OpenAlexaffabout
Kirk R. Smith, Alain Gagnon, Richard Cawthon, Geraldine P. Mineau, Ryan Mazan, Bertrand Desjardins

Bibliographic record

VenueThe Journals of Gerontology Series A · 2009
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsUniversité de MontréalWestern University
FundersNational Institute on AgingHuntsman Cancer Foundation
KeywordsFertilityDemographySisterLongevityReproductionPopulationBiologyGerontologyMedicineGenetics

Abstract

fetched live from OpenAlex

Women giving birth at advanced reproductive ages in natural fertility conditions have been shown to have superior postmenopausal longevity. It is unknown whether improved survival is more likely among relatives of late-fertile women. This study compares survival past age 50 of men with and without a late-fertile sister in two populations: Utahns born in 1800-1869 identified from the Utah Population Database and Québec residents born in 1670-1750 identified from the Programme de recherche en démographie historique. Male survival was greater for those with, rather than without, a sister reproducing after age 45, particularly among men with at least three sisters (Utah rate ratio [RR] = .801, 95% CI = 0.687-0.940; Quebec RR = .786, 95% CI = 0.664-0.931). Survival of wives was unaffected by whether their husbands had a late-fertile sister, suggesting a weak influence of unmeasured socioenvironmental factors. These results support the hypothesis that late female fertility and slow somatic aging may be promoted by the same genetic variants.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.068
GPT teacher head0.350
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

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 designObservational
Domainnot available
GenreEmpirical

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

Citations60
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueThe Journals of Gerontology Series ASame topicReproductive Health and TechnologiesFrench-language works237,207