Egg neglect under risk of predation in Cassin’s Auklet (<i>Ptychoramphus aleuticus</i>)
Bibliographic record
Abstract
We tested predictions concerning the significance of egg neglect for the burrow-nesting seabird Cassin’s auklet (Ptychoramphus aleuticus (Pallas, 1811)) at a colony where endemic Keen’s mice (Peromyscus keeni Merriam, 1897) depredate unattended eggs. A video-camera probe was used to monitor neglect and predation in 32 burrows, and mass loss of incubating adults was measured in 12 separate burrows. Incubating birds lost 8.1% of their body mass over obligate 24 h incubation shifts, suggesting that incubation is costly. In response, most pairs (79%) neglected their egg at least once. As predicted, rates of neglect decreased as incubation progressed, and the costs of neglect increased. Rates of neglect increased during periods of strong winds, which create poor foraging conditions at sea. Contrary to predictions, rates of neglect did not increase when burrows were colder and self-maintenance costs were higher. Neglect was risky in that rates of egg loss by predation increased with frequency of neglect. Increased neglect early in incubation and during periods of poor foraging conditions, despite high rates of predation on neglected eggs, is consistent with the existence of a fitness trade-off between costs and benefits of neglect.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".