Heart rate as a predictor of energy expenditure in undisturbed fasting and incubating penguins
Bibliographic record
Abstract
Heart rate (f(H)) measurement offers the possibility to monitor energy expenditure (EE) in wild animals if the EE/f(H) relationship for the species, physiological stages and activities of interest is known. This relationship has been extensively studied using oxygen consumption rate ( ) measurement in captive, repeatedly handled king penguins (Aptenodytes patagonicus). Unfortunately, the potential effects of stress on the observed relationships resulting from handling and confinement were not considered. This study is the first involving undisturbed animals, and determines the EE/f(H) relationship in naturally fasting and freely incubating or captivity-acclimatized male and female king penguins. EE determination was based on (1) the measurement of body mass loss during periods of phase II fasting, and (2) the calculation of its energy equivalent from changes in body composition, i.e. 23.9 kJ g(-1). f(H) levels in freely incubating and captivity-acclimatized birds were found to be 50-70% lower than those previously reported for resting king penguins during measurements. Significant EE/f(H) relationships were found in freely incubating and captive males and females (R(2)=0.59 to 0.84), with no difference observed between genders. The best overall relationship was obtained by including fasting duration (t, days) in the model: EE=818+43.7xf(H)+36.3t-1.4txf(H) (R(2)=0.91). This equation yielded EE estimates approximately 26% higher than the previously reported 'best' predictive equation in king penguins, and even more so when f(H) was low. This result suggests that stress induces a disproportionate increase of f(H) vs O(2) consumption, and that the use of EE/f(H) relationships obtained in stressed birds could lead to underestimated EE values.
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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 | 0.000 |
| 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".