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Record W4205630194 · doi:10.1093/ornithology/ukab083

Reduced diurnal activity and increased stopover duration by molting Swainson’s Thrushes

2022· article· en· W4205630194 on OpenAlexafffundabout
Ana Morales, Barbara Frei, Greg W. Mitchell, Camille Bégin-Marchand, Kyle H. Elliott

Bibliographic record

VenueThe Auk · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsSte. Anne's HospitalEnvironment and Climate Change CanadaMcGill University
FundersEnvironment and Climate Change CanadaNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsMoultingBiologyEcologyHabitatZoology

Abstract

fetched live from OpenAlex

Abstract Migration consists of a sequence of small- to large-scale flights often separated by stopovers for refueling. Tradeoffs between minimizing migration time (more flights, shorter stopovers) and maximizing energy gain (fewer flights, longer stopovers) will affect overall migration timing. For example, some individuals make long-term stopovers in high-quality habitat that maximize energy gain (e.g., molt-migration), but movement to those habitats likely costs time. We used radio telemetry and blood plasma metabolite levels to examine physiological and behavioral tradeoffs between molt-migrant (birds molting at the molt stopover; n = 59) and post-molt (birds that presumably completed their molt elsewhere; n = 19) migrant Swainson’s Thrushes (Catharus ustulatus) near Montreal, Canada. Molt-migration was a large time investment as the average stopover duration for molt-migrants was of 47 ± 9 days (~13% of the entire annual cycle), almost twice as long as previously assumed from banding records, and far longer than stopovers of post-molting individuals (7 ± 2 days). Daily mortality rate during the molt stopover was similar to the average annual daily mortality rate. Molt-migrants’ circadian rhythms closely matched light levels, whereas post-molting birds had irregular rhythms and averaged 1 hr greater activity per day than molt-migrants. Despite being less active, molt-migrants had similar refueling rates based on metabolite profiles. As compared with migrants that completed molt earlier, molt-migrants at this stopover site had slower subsequent migration rates. Thus, birds using long-term stopovers appeared to tradeoff energy (efficient refueling) for time (slower subsequent migration).

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.469
Threshold uncertainty score0.999

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.219
Teacher spread0.210 · 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.

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

Citations14
Published2022
Admission routes3
Has abstractyes

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