Energy costs of chick rearing in Black-legged Kittiwakes (<i>Rissa tridactyla</i>)
Bibliographic record
Abstract
We studied energy expenditure in adult Black-legged Kittiwakes (Rissa tridoctyla) with doubly labeled water to measure energy costs of chick rearing. We removed eggs from randomly selected nests and compared energy expenditure late in the chick-rearing period between adults raising chicks and adults whose eggs had been removed. Adults raising chicks expended energy at a rate 21% higher than adults from manipulated nests, apparently owing to differences in activity patterns while away from the colony. No sex-specific differences were detected in energy costs of chick rearing or energy expenditure, although statistical power for these analyses was fairly low. Among the unmanipulated group, energy expenditure tended to be positively related to natural brood size. An ancillary goal of our study was to test hypotheses that describe how population-level field metabolic rates (FMRs) vary during chick rearing. We compared FMRs among kittiwakes raising chicks at a colony in Alaska (61°09'N) with those reported for a colony in Norway (76°30'N). FMRs of adults raising chicks were nearly identical at the two colonies, suggesting that adults may have preferred levels of energy expenditure during chick rearing that are relatively invariant with environmental conditions, and that are not adjusted according to adult survival probabilities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".