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Record W2009417461 · doi:10.1139/z03-116

Recruitment sex ratios in gray-tailed voles (<i>Microtus canicaudus</i>) in response to density, sex ratio, and season

2003· article· en· W2009417461 on OpenAlexvenueno aff
Monica L. Bond, Jerry O. Wolff, Sven Krackow

Bibliographic record

VenueCanadian Journal of Zoology · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsnot available
FundersNorthwest Scientific AssociationNational Science Foundation
KeywordsSex ratioBiologyOffspringOperational sex ratioMicrotusPopulationFacultativeSex allocationPopulation densityArvicolinaeDemographyZoologyEcology

Abstract

fetched live from OpenAlex

We tested predictions associated with three widely used hypotheses for facultative sex-ratio adjustment of vertebrates using eight enclosed populations of gray-tailed voles, Microtus canicaudus. These were (i) the population sex ratio hypothesis, which predicts that recruitment sex ratios should oppose adult sex-ratio skews, (ii) the local resource competition hypothesis, which predicts female-biased recruitment at low adult population density and male-biased recruitment at high population density, and (iii) the first cohort advantage hypothesis, which predicts that recruitment sex ratios should be female biased in the spring and male biased in the autumn. We monitored naturally increasing population densities with approximately equal adult sex ratios through the spring and summer and manipulated adult sex ratios in the autumn and measured subsequent sex ratios of recruits. We did not observe any significant sex-ratio adjustment in response to adult sex ratio or high population density; we did detect an influence of time within the breeding season, with more female offspring observed in the spring and more male offspring observed in the autumn. Significant seasonal increases in recruitment sex ratios indicate the capacity of female gray-tailed voles to manipulate their offspring sex ratios and suggest seasonal variation in the relative reproductive value of male and female offspring to be a regular phenomenon.

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)0.001
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 score0.728
Threshold uncertainty score0.907

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.023
GPT teacher head0.255
Teacher spread0.231 · 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.

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

Citations11
Published2003
Admission routes1
Has abstractyes

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