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Record W2809690084 · doi:10.1098/rsbl.2018.0194

Alternative reproductive strategies in white-throated sparrows are associated with differences in parasite load following experimental infection

2018· article· en· W2809690084 on OpenAlexafffund
Rachel J. Boyd, T. R. KELLY, Scott A. MacDougall‐Shackleton, Elizabeth A. MacDougall‐Shackleton

Bibliographic record

VenueBiology Letters · 2018
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBird parasitology and diseases
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyImmunocompetencePlumageSparrowZoologyWhite (mutation)ImmunityParasitismReproductionAndrogenEmberizidaeParasite hostingEcologyOffspringImmune systemImmunologyHost (biology)PregnancyGeneticsEndocrinologyHabitat

Abstract

fetched live from OpenAlex

) are unusual in having two discrete plumage morphs, white-striped and tan-striped. Within each sex, white-striped individuals are more aggressive and provide less parental care than tan-striped individuals. We extended immunocompetence handicap models, which predict sex differences in immunity and parasitism, to hypothesize that infection susceptibility should be greater in white-striped than tan-striped birds. We inoculated birds of both morphs with malarial parasites. Contrary to our prediction, among birds that became infected, parasite loads were higher in tan-striped than white-striped individuals and did not differ between the sexes. Circulating androgen levels did not differ between morphs but were higher in males than females. Our findings are not consistent with androgen-mediated immunosuppression. Instead, morph differences in immunity could reflect social interactions or life-history-related differences in risk of injury, and/or genetic factors. Although plumage and behavioural morphs of white-throated sparrow may differ in disease resistance, these differences do not parallel sex differences that have been reported in animals, and do not appear to be mediated by differences in androgen levels.

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 score0.118
Threshold uncertainty score0.847

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 studies0.0000.001
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 head0.021
GPT teacher head0.282
Teacher spread0.262 · 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

Citations17
Published2018
Admission routes2
Has abstractyes

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