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Record W1987732067 · doi:10.1139/z05-126

Effects of sex and body size on ectoparasite loads in the northern flying squirrel (<i>Glaucomys sabrinus</i>)

2005· article· en· W1987732067 on OpenAlexvenueno aff
Carolina Perez-Orella, Albrecht I. Schulte‐Hostedde

Bibliographic record

VenueCanadian Journal of Zoology · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBiologySexual dimorphismParasite loadZoologyEcologyHost (biology)Immune systemImmunology

Abstract

fetched live from OpenAlex

Ectoparasites can have profoundly negative fitness consequences for host organisms. Sex differences in parasite load have been documented in many mammals, and have been attributed either to the allocation of energy to growth rather than the immune system in mammals exhibiting male-biased sexual size dimorphism or to the immunosuppressive qualities of testosterone. In addition, ectoparasites can have negative effects on body size and condition, as energy is allocated to the immune system rather than to growth and maintenance. Here, we used the northern flying squirrel (Glaucomys sabrinus (Shaw, 1801)) and its ectoparasites to test two predictions: (1) males are more heavily parasitized than females and (2) individuals with high ectoparasite loads will be in poorer condition and be smaller than individuals with low ectoparasite loads. Males were significantly more parasitized than females, and there was a nonsignificant trend for small males to be more parasitized than large males. Because the northern flying squirrel is not sexually dimorphic, the immunosuppressive qualities of testosterone may explain the sex differences in ectoparasite load. Ectoparasites may also influence skeletal growth rates, and males that are more susceptible to ectoparasites may simply be unable to allocate as much energy to growth and are thus structurally smaller.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.258
Threshold uncertainty score0.752

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 head0.006
GPT teacher head0.216
Teacher spread0.210 · 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

Citations60
Published2005
Admission routes1
Has abstractyes

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