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Record W199049872

An isotopic assessment of protein from diet and endogenous stores: Effects on egg production and incubation behaviour of geese

2006· article· en· W199049872 on OpenAlexaboutno aff
Joel A. Schmutz, Keith A. Hobson, Julie A. Morse

Bibliographic record

VenueArdea · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
Fundersnot available
KeywordsAnatidaeGooseBrantaBiologyNest (protein structural motif)IncubationWaterfowlNutrientEcologyDeltaIsotope analysisZoologyHabitat
DOInot available

Abstract

fetched live from OpenAlex

Little empirical information exists to assess to what degree geese use a capital versus income breeding strategy for investing nutrients into eggs. We used stable isotope methods to directly estimate the sources of protein deposited into egg yolks of Brent Branta bernicla and Emperor Geese Anser canagicus on the Yukon-Kuskokwim Delta, Alaska, USA. Approximately 59 and 45% of protein in egg yolks of Brent and Emperor Geese, respectively, was derived from exogenous sources (i.e. food plants on the local breeding area). Within clutches of Brent Goose eggs, first-laid eggs exhibited slightly higher contributions from endogenous reserves than last-laid eggs. This pattern was less clear for Emperor Geese, which may have been a consequence of possibly analysing eggs that were laid by intraspecific nest parasites rather than by hosts. For both these species, individuals exhibited large variability in the percent contribution of exogenous versus endogenous stores to eggs, and future studies should identify ecological factors related to this variation. Those Emperor Geese in poor body condition incubated their nests less constantly, and based on δ 13 C values, they fed on terrestrial foods while off their nests. Although not a pure capital breeder, Emperor Geese used nutrients garnered on spring staging areas to fuel virtually all their own maintenance during incubation and to contribute half or more of the nutrients in eggs. These results highlight the ecological importance of these spring staging habitats to geese.

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 score0.084
Threshold uncertainty score0.228

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 head0.008
GPT teacher head0.236
Teacher spread0.228 · 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

Citations54
Published2006
Admission routes1
Has abstractyes

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