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Record W82964910

Dietary ecology of the Glaucous-winged Gull (Larus glaucescens) in the Pacific North-West: conventional and stable isotope techniques and implications for eco-toxicology monitoring

2013· dissertation· en· W82964910 on OpenAlexaboutno aff
Mikaela L. Davis

Bibliographic record

VenueSummit (Simon Fraser University) · 2013
Typedissertation
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsEcologyGeographyEnvironmental scienceBiology
DOInot available

Abstract

fetched live from OpenAlex

Effective use of seabirds in ecotoxicology monitoring programs (e.g. Canada’s Chemical Management Plan) requires detailed knowledge of their ecology. I examined the dietary ecology of Glaucous-winged Gulls (Larus glaucescens) in British Columbia, using conventional diet analysis and stable isotope analysis. Conventional analysis suggests that gulls forage in an opportunistic manner, with a variety of prey types consumed at a colony closest to urban development, but that marine sources (fish, invertebrates) were the predominant dietary component at all colonies. However, variation in chick diet between 2009 and 2010 indicates that diet can vary considerably on a short time scale. Compared with historical records, gulls currently consume less food from anthropogenic sources and more fish in the Salish Sea, whereas at Cleland Island diet has remained marine-based over time. Stable isotope analysis confirmed that gulls at all three monitored colonies fed primarily on near-shore marine prey at a high trophic level.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.464
Threshold uncertainty score0.922

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
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 head0.011
GPT teacher head0.224
Teacher spread0.213 · 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 source (direct Gemma or distilled Codex), 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
Published2013
Admission routes1
Has abstractyes

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