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Seasonal changes in sexual size dimorphism in northern chamois

2011· article· en· W1924523127 on OpenAlexafffund
Marco Rughetti, Marco Festa‐Bianchet

Bibliographic record

VenueJournal of Zoology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsCenter for Northern StudiesUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSexual dimorphismBiologyPolygynyZoologySexual selectionSex characteristicsEcologyDemographyEndocrinologyPopulation

Abstract

fetched live from OpenAlex

In many polygynous mammals, sexual size dimorphism (SSD) is thought to have evolved through sexual selection, because larger males prevail in male–male combat and secure access to estrous females. SSD is often correlated with higher age-specific mortality of males than of females, possibly because males have higher nutritional requirements and riskier growth and reproductive tactics. In adult chamois Rupicapra rupicapra, sexual dimorphism in skeletal size was about 5%, but dimorphism in body mass was highly seasonal. Males were about 40% heavier than females in autumn but only 4% heavier in spring. For a given skeletal size, males were heavier than females only in autumn. Chamois sexual dimorphism appears mainly due to greater summer accumulation of fat and muscle mass by males than by females. Male mass declines rapidly during the rut. Limited dimorphism in skeletal size combined with substantial but seasonal dimorphism in mass has not been reported in other sexually dimorphic ungulates. Seasonal changes in mass allow males to achieve large size for the rut by accumulating body resources during summer. The use of these resources over the rut may reduce mortality associated with sustaining a large size over the winter.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.999

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)0.0020.000

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 head0.019
GPT teacher head0.212
Teacher spread0.194 · 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 teacher head, not a consensus.

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

Citations42
Published2011
Admission routes2
Has abstractyes

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