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BODY TEMPERATURE AND RESTING BEHAVIOR OF GREATER SNOW GOOSE GOSLINGS IN THE HIGH ARCTIC

2000· article· en· W2179033846 on OpenAlexaff
Daniel Fortin, Gilles Gauthier, Jacques Larochelle

Bibliographic record

VenueOrnithological Applications · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsCenter for Northern StudiesUniversité Laval
Fundersnot available
KeywordsSnowPrecocialHomeothermyThermoregulationBiologyGooseAnimal scienceEcologyArcticMeteorology

Abstract

fetched live from OpenAlex

We examined the control of body temperature during active and resting behaviors in chicks of a large precocial bird, the Greater Snow Goose (Chen caerulescens atlantica), growing in a cold Arctic environment. Imprinted goslings from 4 to 31 days old maintained their mean (± SD) body core temperature within a narrow range around 40.6 ± 0.2°C (range: 38.7–42.2°C), independently of changes in their thermal environment. Average body temperature increased <0.4°C between 4 and 31 days of age. Hypothermia, potentially an energy-saving mechanism, was not used by active goslings. The potential for heat loss to the environment influenced the length of resting bouts in wild goslings. As environmental temperature increased, wild goslings remained sitting alone for longer periods, whereas when it decreased, brooding behavior was prolonged. The time spent huddling increased with the number of goslings involved. Body temperature during huddling bouts measured in imprinted chicks was significantly lower than during periods of activity, showing a rapid decrease averaging 0.8°C at the onset of huddling, followed by a slow recovery before activity was resumed. Thus, huddling behavior was not used as a rewarming mechanism. Greater Snow Goose goslings appear to prioritize metabolic activity by maintaining a high body temperature, despite the high energy costs that may be involved. Social thermoregulation is used to reduce the energy costs entailed by the strict maintenance of homeothermy.

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 score0.436
Threshold uncertainty score0.497

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 head0.021
GPT teacher head0.242
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 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

Citations17
Published2000
Admission routes1
Has abstractyes

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