Survival and nesting success of the Pacific Eider (Somateria mollissima v-nigrum) near Bathurst Inlet, Nunavut
Bibliographic record
Abstract
We used resighting data from 242 individually marked females to estimate apparent survival of Pacific Eiders ( Somateria mollissima v-nigrum Bonaparte, 1855) at a nesting colony in central arctic Canada from 2001 to 2007. In addition, we used data from nest searches conducted on islands at a freshwater lake and an adjacent marine environment to estimate annual breeding success. Annual survival rate estimates ranged from 0.84 ± 0.04 (mean ± SE) to 0.86 ± 0.05. Mayfield estimates of nest success ranged from 48.8% to 68.1% at the freshwater colony, and from 13.9% to 43.5% at the marine nesting colonies. The overwhelming cause of nest failure at both nesting areas was predation by grizzly bear ( Ursus arctos horribilis Ord, 1815), arctic fox ( Vulpes lagopus (L., 1758)), and wolverine ( Gulo gulo (L., 1758)). The majority of nests were initiated prior to ocean ice breakup in mid-July, thus mammalian predators had access to the islands well into incubation. Our results suggest that during the period from 2001 to 2007, the population of Pacific Eiders was likely not in decline. Therefore, the marked decline observed for eiders migrating past Point Barrow, Alaska, from 1976 to 1996 was more likely attributable to a stochastic event, such as unfavourable ice conditions, than to a chronic factor.
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 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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".