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Record W2104314240 · doi:10.1139/z2012-047

Nutritional stress and body condition in the Great Gray Owl (<i>Strix nebulosa</i>) during winter irruptive migrations

2012· article· en· W2104314240 on OpenAlexvenueno aff
Gary R. Graves, Seth D. Newsome, David E. Willard, David A. Grosshuesch, William W. Wurzel, Marilyn L. Fogel

Bibliographic record

VenueCanadian Journal of Zoology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsBiologySexual dimorphismPredationZoologyContext (archaeology)Ecology

Abstract

fetched live from OpenAlex

The largest irruptive migration of the Great Gray Owl ( Strix nebulosa Forster, 1772) recorded since 1831 occurred in Minnesota, USA, during the winter of 2004–2005. We tested the hypothesis that morphometric indicators of nutritional stress covary with stable isotope signatures in a sample of 265 owls killed by vehicle collisions. The ratio of carbon to nitrogen in muscle (C/Nmuscle) was shown to be a reliable proxy of nutritional stress. δ13C values for liver and muscle were significantly higher in owls in poor condition, reflecting the depletion of lipid reserves in fasting individuals. On the other hand, δ15N values for liver and muscle were marginally lower or unchanged in owls in poor condition. Stomachs of emaciated owls were less likely to contain prey, implying that many nutritionally stressed individuals were too weak to hunt and were near the tipping point of irreversible fasts. In a broader context, sexual differences in the correlative relationships between stable isotope signatures, C/N, and body condition suggest that the consequences of reversed sexual size dimorphism extend to physiological processes during the nonbreeding season.

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 score0.031
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

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 head0.224
Teacher spread0.216 · 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

Citations21
Published2012
Admission routes1
Has abstractyes

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