Nest-site materials affect nest-bowl use by Common Eiders (<i>Somateria mollissima</i>)
Bibliographic record
Abstract
Nest-site characteristics influence reproductive success in birds. Most studies of nest-site selection evaluate nest characteristics following the commencement of egg-laying, possibly overlooking the importance of pre-existing nest-site features that may be altered during the nesting process. Because Common Eiders ( Somateria mollissima (L.,1758)) often lay their eggs in nest bowls created in previous years, we were able to experimentally place moss or feather down in nest bowls prior to nesting. We then quantified whether these materials increased nest establishment or advanced laying dates relative to control nests and nests where material was removed prior to arrival of nesting females. We found no difference in the likelihood of successful nest establishment between groups. However, the onset of incubation occurred 2–3 days earlier in nest bowls that contained feather down versus nest bowls with little or no nesting material. Nest bowls containing feathers or vegetation may be selected first if they increase nest survival, perhaps by enhancing egg concealment during the critical early-laying period. The presence of material for egg concealment may be particularly important in nesting environments where tall or dense vegetation is not available to provide nest cover.
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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) | 0.002 | 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".