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Record W2076349522 · doi:10.1126/science.1235765

Density Triggers Maternal Hormones That Increase Adaptive Offspring Growth in a Wild Mammal

2013· article· en· W2076349522 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueScience · 2013
Typearticle
Languageen
FieldPsychology
TopicNeuroendocrine regulation and behavior
Canadian institutionsMcGill UniversityThe Scarborough HospitalUniversity of TorontoUniversity of AlbertaUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsOffspringBiologyMaternal effectMammalPopulationGlucocorticoidSelection (genetic algorithm)Natural selectionAdaptive responseZoologyEcologyEndocrinologyDemographyPregnancyGenetics

Abstract

fetched live from OpenAlex

In fluctuating environments, mothers may enhance the fitness of their offspring by adjusting offspring phenotypes to match the environment they will experience at independence. In free-ranging red squirrels, natural selection on offspring postnatal growth rates varies according to population density, with selection favoring faster-growing offspring under high-density conditions. We show that exposing mothers to high-density cues, accomplished via playbacks of territorial vocalizations, led to increased offspring growth rates in the absence of additional food resources. Experimental elevation of actual and perceived density induced higher maternal glucocorticoid levels, and females with naturally or experimentally increased glucocorticoids produced offspring that grew faster than controls. Therefore, social cues reflecting population density were sufficient to elicit increased offspring growth through an adaptive hormone-mediated maternal effect.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.531

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 head0.030
GPT teacher head0.291
Teacher spread0.260 · 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