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Record W2155226172 · doi:10.1093/beheco/ars225

Stopover refueling rate underlies protandry and seasonal variation in migration timing of songbirds

2013· article· en· W2155226172 on OpenAlexaff
Chad L. Seewagen, Christopher G. Guglielmo, Yolanda E. Morbey

Bibliographic record

VenueBehavioral Ecology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsWestern University
Fundersnot available
KeywordsBiologyJuvenileSpring (device)Akaike information criterionEcologyZoologyStatisticsEngineering

Abstract

fetched live from OpenAlex

We used plasma metabolite analysis to assess refueling rates of songbirds at stopover sites in New York and test hypotheses that males refuel faster than females during spring (in 2 species), migrants refuel faster during spring than autumn (in 5 species), and adults refuel faster than juveniles during autumn (in 4 species). Model selection based on Akaike’s information criterion indicated that males had higher refueling rates than females during spring in both species tested. Spring migrants had higher refueling rates than autumn migrants in 4 of the 5 species we examined. Juvenile and adult refueling rates during autumn did not differ in any species. Our results indicate that variation in stopover refueling rate can operate as a mechanism for protandry in spring and faster migration during spring than autumn. We found no evidence that juvenile refueling performance during autumn was poorer than that of adults.

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)0.001
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.022
GPT teacher head0.265
Teacher spread0.244 · 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

Citations67
Published2013
Admission routes1
Has abstractyes

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