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Record W2021396343 · doi:10.1676/05-001.1

VARIATION IN SIZE AND COMPOSITION OF BUFFLEHEAD (BUCEPHALA ALBEOLA) AND BARROW'S GOLDENEYE (BUCEPHALA ISLANDICA) EGGS

2006· article· en· W2021396343 on OpenAlexafffund
Jennifer L. Lavers, J. E. Thompson, Cynthia A. Paszkowski, C. Davison Ankney

Bibliographic record

VenueThe Wilson Journal of Ornithology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsWestern UniversityUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Alberta
KeywordsAllometryYolkNutrientBiologyAnimal scienceZoologyEcology

Abstract

fetched live from OpenAlex

We investigated the relationships between egg nutrient constituents and fresh egg mass in Bufflehead (Bucephala albeola) and Barrow's Goldeneye (B. islandica). We found consistently positive relationships between egg mass and yolk, albumen, lipid, mineral, and water (absolute amounts); however, the proportions of nutrient components to fresh mass were highly variable in the eggs of both species (allometric relationships). In Bufflehead eggs, all components except mineral exhibited negative allometry with fresh egg mass. In Barrow's Goldeneye eggs, only mineral exhibited negative allometry, whereas yolk, lipid, and water all exhibited positive allometry with fresh egg mass. Overall, larger eggs of both species contained greater absolute amounts of nutrients; therefore, larger eggs were of better quality than smaller eggs. Nutrient content, however, was more highly correlated with mass in Barrow's Goldeneye eggs than in Bufflehead eggs. We propose that this may be due to the source of egg nutrients: because of their smaller body size, Buffleheads typically rely more on exogenous nutrients than Barrow's Goldeneyes.

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 score0.075
Threshold uncertainty score0.399

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 head0.005
GPT teacher head0.227
Teacher spread0.222 · 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

Citations2
Published2006
Admission routes2
Has abstractyes

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