Molt Migration in Relation to Breeding Success in Greater Snow Geese
Bibliographic record
Abstract
We describe summer migratory movements by female greater snow geese (Chen caerulescens atlantica) breeding on Bylot Island, Nunavut. We followed 121 radio-collared females between 1997 and 2001 to determine the frequency and timing of their departure from the colony in relation to breeding status, nesting success, and molting chronology. We found that 90% (n = 51) of non-breeders (no nest found) and 97% (n = 29) of failed nesters (nest destroyed or abandoned before hatch) departed the island before molting. The few non-breeders that remained on Bylot Island all summer molted earlier than adults with young, and they appeared to initiate the fall migration before breeding geese. In contrast, only 2% of successful nesters (n = 41) left Bylot Island to molt, and those that did presumably had lost their offspring in the early stages of brood rearing. Thus, the occurrence of a molt migration in greater snow geese appears to be strongly dependent on reproductive status and nesting success. The area used by molt migrants and their habitat requirements during molt remain unknown. We suggest that the paucity of predator-safe areas (such as large water bodies) on Bylot Island may be an important factor that drives the geese to molt elsewhere.
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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 | 0.001 |
| 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".