Breeding Biology of Olrog's Gull in Bahía Blanca Estuary, Argentina
Bibliographic record
Abstract
Aspects of the breeding biology of the world largest Olrog's Gull (Larus atlanticus) colony, in the estuary of Bahía Blanca, Argentina, were assessed for 101, 66, and 47 nests in 2005, 2006, and 2007, respectively. Mean (± SD) clutch size in 2005 was 1.86 ± 0.73 eggs per nest and modal clutch size was two eggs (range = 1–3). The incubation period was 1.67 days longer for A-eggs than for B-eggs (27.44 ± 1.22 days vs. 25.77 ± 1.36 days, respectively; P < 0.001). Incubation length for C-eggs was 25.75 ± 0.96 days. The largest eggs were 31.5% (length), 21.3% (breadth), and 66.5% (volume) larger than the smallest eggs. Mean egg volume in 2006 and 2007 decreased with hatching order, but the magnitude of this change was more pronounced in 2007 than in 2006. Variation in all egg measurements was larger among than within clutches. Hatching success within three-egg clutches was 76.9% in 2005, 81.7% in 2006, and 91.3% in 2007 (P = 0.20). Total egg loss in 2005 reached 16.7% and complete clutch loss was 43.8% during the incubation period. Parameters quantified in this study provide a comparative benchmark for future research on factors affecting breeding parameters in Olrog's Gull from this and other colonies, and lay the foundation for developing effective conservation strategies for the species.
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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 | 0.000 | 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".