The pilfering of puffins: behavioural tactics of herring gulls and Atlantic puffins during kleptoparasitic competition
Bibliographic record
Abstract
Kleptoparasitism is a foraging strategy whereby an individual steals a procured food item from another individual. Individuals can optimize their kleptoparasitic foraging strategy by modifying their behaviour to expend less energy than they would by foraging independently or by attacking more profitable hosts. Individuals vulnerable to becoming a host to a kleptoparasite can modify their behaviour to reduce the risk of losing prey to a kleptoparasite by using tactics such as handling food in areas inaccessible to the kleptoparasite or landing in groups. Observations of individual herring gulls (Larus argentatus) and approaches to the burrow slope by Atlantic puffins (Fratercula arctica) were conduced in summer 2018 on Gull Island, Newfoundland and Labrador. The findings of this study suggest that herring gulls optimize their kleptoparasitic foraging strategy by targeting more profitable hosts, and that puffins at risk of kleptoparasitism effectively mitigate their risk by engaging in evasive behaviour.
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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 | 0.001 | 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".