Composition of Eggs and Neonates of Canada Geese and Lesser Snow Geese
Bibliographic record
Abstract
We collected eggs, neonates, and adults of Canada Geese (Branta canadensis interior) and Lesser Snow Geese (Chen caerulescens caerulescens) from Akimiski Island, Nunavut, during the 1996 breeding season. This was done to assess interspecific differences in egg composition, egg-nutrient catabolism, developmental maturity, tissue maturity, and body reserves, and to relate observed differences in those variables to ecological conditions historically experienced by Canada Geese and Lesser Snow Geese. Eggs of both species had identical proportional compositions, but Canada Goose embryos catabolized 13% more of their egg protein, whereas Lesser Snow Goose embryos catabolized 9% more of their egg lipid. Neonate Canada Geese and Lesser Snow Geese had similar protein reserves, relative to body size, but Lesser Snow Geese had relatively smaller lipid reserves than did Canada Geese. Relative to conspecific adults, Lesser Snow Goose goslings generally were structurally larger at hatch than were Canada Goose goslings. Neonate Lesser Snow Geese had more developmentally mature keels, wings, and breast muscles, and larger gizzards and caeca for their body size, than did neonate Canada Geese. Despite hatching from smaller eggs and having a shorter period of embryonic growth, skeletal muscles and gizzard tissues of Lesser Snow Geese were more functionally mature than those of Canada Geese. Increased lipid use during embryonic development could account for how Lesser Snow Geese hatched in a more developmentally and functionally mature state. In turn, differences in developmental and functional maturity of Lesser Snow Geese, as compared to Canada Geese, likely are adaptations that offset metabolic costs associated with their small body size, or to selection pressures associated with high arctic environmental conditions and colonial nesting and brood rearing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".