BODY TEMPERATURE AND RESTING BEHAVIOR OF GREATER SNOW GOOSE GOSLINGS IN THE HIGH ARCTIC
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".