Incubation behaviour of greater snow geese in relation to weather conditions
Bibliographic record
Abstract
Based on allometric considerations, goose species with larger body masses should spend more time on their nest during incubation than smaller ones. We documented hourly and daily variations in incubation behaviour of large goose species nesting in the Arctic, the greater snow goose (Chen caerulescens atlantica), and examined the effect of weather conditions on recess frequency and duration. Incubation behaviour was inferred from variations in temperature recorded by adding artificial eggs to clutches. Mean nest attentiveness during the incubation period was 91.4%, indicating that it can be relatively low even for a large goose. Females took 56 recesses/day, which lasted for an average of 22.7 min each. Variability in incubation behaviour over time was greater within females than among females. Recesses were more frequent, and of longer duration, in the afternoon than at night. Females were also less attentive to their nest as incubation progressed, a consequence of both an increase in recess frequency and duration, except in the days before hatching, when nest attentiveness rose abruptly. The relatively low nest attendance of incubating greater snow geese may be a consequence of the opportunity to feed close to the nest during recesses. Weather parameters influenced movements away from the nests in 11 of the 12 females monitored. Females took more recesses when wind velocity was low and, to a lesser extent, when air temperature and solar radiation were high, but the response was quite variable among females. Although females seem to adjust their behaviour in order to limit egg cooling, variations in risk of predation according to time of day may also influence incubation patterns.
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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) | 0.001 | 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".