Nesting Habitat Use by Common Eiders on Stratton Island, Maine
Bibliographic record
Abstract
We examined nesting habitat use of Common Eiders (Somateria mollissima dresseri) breeding on Stratton Island, Maine in 2004 and 2005. Eiders generally avoided low-lying, open vegetation, and nested in dense, structurally complex habitats. The three most common habitat types used were Asiatic bittersweet (Celastrus orbiculata) patches, red raspberry (Rubus idaeus) thickets, and forest (primarily Malus pumila and Prunus virginiana). Nest densities were highest in bittersweet (> 500 nests/ha). Eiders had little nest predation by Larus gulls, and apparent nest success was high in all three habitats (bittersweet: 82–89%, raspberry: 87%, forest: 58–72%). Eiders appeared to select nest sites adaptively to avoid detection or access by predators, although other factors such as nest microclimate, female quality or condition, and energetic demands during incubation may also be important.
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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 | 0.001 | 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".