Morphological Variation Among Herring Gulls (Larus Argentatus) And Great Black-Backed Gulls (Larus Marinus) In Eastern North America
Bibliographic record
Abstract
Herring Gull (Larus argentatus) and Great Black-backed Gull (L. marinus) morphometric data from various eastern North American locations was collected to examine the sources of variation in body size within and among geographic regions. For Herring Gulls, significant differences in all commonly taken measurements at local and regional scales were found. However, most of the variation in measurements was due to sex differences and the natural variance seen within local populations. Herring Gulls breeding in the Arctic did not show any evidence of being morphologically different from other groups. A discriminant function derived from a Newfoundland, Canada, breeding population of Herring Gulls successfully assigned the sex of birds in Atlantic Canada and Nunavut, Canada, further emphasizing that most of the variation seen is between sexes and not among local or even regional populations. It also indicates that the evitable variation introduced by inter-individual differences in measurements was insufficient to compromise the utility of the discriminant function. The correct classification rate was lower for Great Lakes breeding Herring Gulls, indicating that these birds have different morphologies than those of populations in easterly regions. In contrast, few differences and no clear geographic patterns were found in measurements for Great Black-backed Gulls. These results were consistent with recent genetic information, suggesting an older west to east radiation of Herring Gulls across North America and a lack of isolation among Great Black-Backed Gull populations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".