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Record W2316926239 · doi:10.1095/biolreprod.115.129833

Benefits of Menopause: Good Fishing

2015· letter· en· W2316926239 on OpenAlexaboutno aff
Charlotte Schubert

Bibliographic record

VenueBiology of Reproduction · 2015
Typeletter
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
Fundersnot available
KeywordsWhaleOffspringBiologyMenopauseDemographyEcologySociology

Abstract

fetched live from OpenAlex

Humans can't understand whale communication, but if they did, they might hear this familiar refrain: “Give Grandma some respect; she has been around!" Post-menopausal killer whales (Fig. 1) are community leaders, with expertise in finding food when the salmon runs are poor, suggests an analysis of 751 hours of videos of resident whales in Washington and British Columbia [1]. The findings hint that the transfer of ecological knowledge to kin by older females may have partly driven the evolution of menopause. Resident orca whales in the Salish sea. Everyone stays with the family! Image courtesy NOAA. In only a handful of species do the females survive for decades after their reproductive years—humans, pilot whales, and killer (orca) whales. In humans, several studies have showcased the fitness benefits of being a grandmother—for instance, pre-modern Finnish and Canadian women who lived long lives had more grandchildren than women who died soon after menopause. As with human hunter-gatherer groups (our evolutionary crucible), the resident orca whales of Puget Sound and British Columbia have a tight-knit society. And perhaps whale bonds are even tighter—human hunter-gatherer girls and women were thought to eventually leave the group, say the researchers, whereas female and male whale offspring do not leave their mother's pod. Previous studies have shown that adult whales are much more likely to die in the year after their mother's death. In the new study, Lauren Brent et al. identified one key way older females contribute to the fitness of their offspring. They found that older females were much more likely than other whales to lead pods as they roamed through coastal waters, trolling for salmon—their primary source of food. What's more, during years when salmon runs were scarce, the fraction of older females leading pods increased substantially. The findings suggest that older females serve as a repository of ecological information, enabling whales to survive when food is scarce. As a female ages, her relatedness to her group increases as her offspring reproduce, and her accumulated knowledge in turn benefits these kin. Whales have complex, fluid societies, which humans barely understand. For instance, some orca whales—not part of this study—live in migratory groups that hunt seals. As another example, male whales, who rarely live past 50, seem more dependent on their mothers than do females, and are more likely to die after she dies. Perhaps mom puts more resources into males since they mate outside the pod, increasing her reproductive success with less strain on the pod's food resources, speculate the researchers. It is likely that menopause is about more than finding food, say the researchers. Throughout the long lives of these sophisticated creatures, older female whales may help younger animals navigate a complex range of social and environmental situations.

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)0.007
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: Editorial · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.001

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 head0.037
GPT teacher head0.253
Teacher spread0.216 · 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
GenreEditorial

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".

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Citations2
Published2015
Admission routes1
Has abstractyes

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