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Record W2028510358 · doi:10.1139/z08-133

Parental allocation of additional food to own health and offspring growth in a variable environment

2009· article· en· W2028510358 on OpenAlexvenueno aff
Patrik Karell, Hannu Pietiäinen, Heli Siitari, Tuomo Pihlaja, Pekka Kontiainen, Jon E. Brommer

Bibliographic record

VenueCanadian Journal of Zoology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsnot available
Fundersnot available
KeywordsOffspringBiologyReproductionVoleNest (protein structural motif)EcologyLife history theoryLife historyParental investmentZoologyDemographyPregnancyPopulation

Abstract

fetched live from OpenAlex

Life-history theory predicts increased investment in current reproduction when future reproduction is uncertain and a more balanced investment in current and future reproduction when prospects for both are good. The outcome of the balance in parental allocation depends on which life-history component maximizes the fitness benefits. In our study system, a 3-year vole cycle generates good prospects of current and future reproduction for Ural owls ( Strix uralensis Pallas, 1771) in increase vole phases and uncertain prospects in decrease vole phases. We supplementary-fed Ural owls during the nestling period in 2002 (an increase phase) and 2003 (a decrease phase), and measured offspring growth, parental effort, and physiological health by monitoring haematocrit, leucocyte profiles, intra- and inter-celluar blood parasites, and (in 2003) humoral antibody responsiveness. Food supplementation reduced parental feeding rate in both years, but improved a female parent’s health only in 2002 (an increase phase) and had no effects on males in either year. Nevertheless, supplementary-fed offspring reached higher asymptotic mass and fledged earlier in both years. Furthermore, early fledging reduced offspring exposure to blood-sucking black flies (Diptera, Simuliidae) in the nest. We discuss how parental allocation of resources to current and future reproduction may vary under variable food conditions.

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 score0.021
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 head0.011
GPT teacher head0.208
Teacher spread0.197 · 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

Citations27
Published2009
Admission routes1
Has abstractyes

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