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Record W1992900273 · doi:10.1038/srep01816

Arctic-nesting birds find physiological relief in the face of trophic constraints

2013· article· en· W1992900273 on OpenAlexafffundabout
Laura McKinnon, Erica Nol, Cédric Juillet

Bibliographic record

VenueScientific Reports · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsTrent University
FundersNatural Sciences and Engineering Research Council of CanadaChurchill Northern Studies Centre
KeywordsNesting (process)Trophic levelArcticEcologyFace (sociological concept)The arcticGeographyComputer scienceZoologyBiologyOceanographyGeologyEngineering

Abstract

fetched live from OpenAlex

A climate-induced phenological mismatch between the timing of reproduction and the timing of food resource peaks is one of the key hypothesized effects of climate change on wildlife. Though supported as a mechanism of population decline in birds, few studies have investigated whether the same temperature increases that drive this mismatch have the potential to decrease energetic costs of growth and compensate for the potential negative effects of reduced food availability. We generated independent indices of climate and resource availability and quantified their effects on growth of Dunlin (Calidris alpina) chicks, in the sub-arctic tundra of Churchill, Manitoba during the summers of 2010-2011 and found that when resource availability was below average, above average growth could be maintained in the presence of increasing temperatures. These results provide evidence that chicks may find physiological relief from the trophic constraints hypothesized by climate change studies.

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 score0.005
Threshold uncertainty score0.010

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)0.0010.000

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 head0.244
Teacher spread0.222 · 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

Citations39
Published2013
Admission routes3
Has abstractyes

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