Red knots (<i>Calidris canutus islandica</i>) manage body mass with dieting and activity
Bibliographic record
Abstract
Mass regulation is birds is well documented. For example, birds can increase body mass in response to lower availability and/or predictability of food and decrease body mass in response to increased predation danger. Birds also demonstrate an ability to maintain body mass across a range of food qualities. Although the adaptive significance of mass regulation has received a great deal of theoretical and empirical attention, the mechanisms by which birds achieve this have not. Several non-exclusive mechanisms could facilitate mass regulation in birds. Birds could regulate body mass by adjusting food intake (dieting), activity, baseline energetic requirements (basal metabolic rate, or BMR), mitochondrial efficiency, or assimilation efficiency. Here, we present the results of two experiments in captive red knots (Calidris canutus islandica) that assess three of these proposed mechanisms: dieting, activity, and up/down-regulation of metabolic rate. In the first experiment, knots were exposed to cues of predation risk that led them to exhibit presumably adaptive mass loss. In the second experiment, knots maintained constant body mass despite being fed on alternating high- and low-quality diets. In both experiments, regulation of body mass was achieved through a combination of changes in food intake and activity. Both experiments also provide some evidence for a role of metabolic adjustments. Taken together, these two experiments demonstrate that fine-scale management of body mass in knots is achieved through multiple mechanisms acting simultaneously.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".