Data for: Fatty acid composition of the red blood cells and cerebral hemispheres of breeding ring-billed gulls (Larus delawarensis) in Newfoundland, Canada.
Bibliographic record
Abstract
Background: Dataset for the experiment looking at whether a greater consumption of omega-3 fatty acids (natural or supplemented intake) improves the problem-solving skills of wild breeding ring-billed gulls. The experiment took place at 2 ring-billed gull colonies of Newfoundland during their 2021 incubation period (May-June). The Long Pond colony in Conception Bay South is considered urban with gulls mainly foraging on anthropogenic foods poor in omega-3s. The Salmonier colony in Newbridge is considered remote with gulls mainly foraging on marine organisms rich in omega-3s. Upon the beginning of each colony's incubation period, active nests were targeted to receive daily supplementation for 21 days. At Long Pond, 30 nests were supplemented with fish oil rich in omega-3s, 30 nests were given coconut oil as a caloric equivalent devoid of omega-3s, and 30 nests were visited daily but not given any supplement (negative control). At Salmonier, 30 nests were given the coconut supplement and 30 nests were used as negative controls; the fish oil treatment was not implemented at Salmonier since gulls nesting there already consume high levels of omega-3s naturally. At the end of the respective colonies’ incubation period, a cognitive test was deployed at each targeted nest 6 times over 3 days and video-recorded to test the gulls' problem-solving skills. Once the trials were completed, gulls from targeted nests were captured to collect blood and brain samples. The fatty acid composition of the red blood cell fraction and cerebral hemispheres of gulls sampled was characterized by gas chromatography using the CREAIT Network facilities at Memorial University.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.028 | 0.007 |
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".