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Record W2770537495 · doi:10.1642/auk-17-79.1

Seasonal variation in chronic stress and energetic condition in Gray Catbirds (<i>Dumetella carolinensis</i>) and Song Sparrows (<i>Melospiza melodia</i>)

2017· article· en· W2770537495 on OpenAlexaboutno aff
Meghan C. Oberkircher, Susan Smith Pagano

Bibliographic record

VenueThe Auk · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyUric acidPhysiological conditionSeasonalitySeasonal breederEcologyZoologyEndocrinology

Abstract

fetched live from OpenAlex

Migration and the breeding season are periods in which birds face many physical and energetic challenges that may cause changes in stress levels and body condition. Gray Catbirds (Dumetella carolinensis) and Song Sparrows (Melospiza melodia) were captured in 3 consecutive seasons—spring migration, the summer breeding period, and fall migration—in 2014 at a long-term bird-banding station located on the south shore of Lake Ontario to determine patterns of chronic stress and physiological condition related to seasonal shifts in their annual cycles. The heterophil/lymphocyte (H/L) ratio was used to assess chronic stress; and plasma metabolite concentrations (triglyceride and uric acid), along with a scaled body mass index, were used as indicators of the physiological condition and fuel utilization of Gray Catbirds and Song Sparrows. Plasma triglycerides were highest during migration periods for Gray Catbirds, while plasma uric acid was greater in spring and summer than in fall, indicating a seasonal shift in diet, possibly related to seasonal fruit availability. Gray Catbirds had elevated H/L ratios during spring, which suggests that spring migration is a period of modest stress for this species, and this spring stress seemed to be predominantly associated with earlier migration passage through the area. Our results suggest that physiological and immune function can vary across seasons in these species, perhaps in parallel with factors related to food availability at stopover or breeding sites during different times of the year.

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 score0.016
Threshold uncertainty score0.973

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 head0.009
GPT teacher head0.238
Teacher spread0.230 · 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

Citations8
Published2017
Admission routes1
Has abstractyes

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