Shifts in Metabolic Demands in Growing Altricial Nestlings Illustrate Context‐Specific Relationships between Basal Metabolic Rate and Body Composition
Bibliographic record
Abstract
Basal metabolic rate (BMR) in animals is interpreted as reflecting the size and metabolic intensity of energy-consuming tissues. However, studies investigating relationships between the mass of specific organs and interindividual variation in BMR have produced inconsistent patterns with regard to which organs have the largest impact on BMR variation. Because of the known flexibility in organ mass and metabolic intensity within individual organs, relationships between BMR and body-composition variables are bound to be context specific. Altricial nestlings are excellent models to illustrate this phenomenon because of the extreme variation in body composition occurring during growth. Using European starlings at three age classes, we studied changes in body composition together with its effect on variation in resting metabolic rate (RMR) in order to highlight the context-specific nature of these relationships. Our data suggest a transition in metabolic costs during growth in starling nestlings. During the linear phase of growth, energy is mainly consumed by tissue-synthesis processes, with fast-growing organs having a large influence on RMR. In the plateau phase of growth, the energy expenditure is transferred to functional costs, with high-intensity organs having a predominant effect on RMR variation. Our data illustrates the context-specific nature of organ mass-metabolic rate correlations, which complicates inter- and intraspecific comparisons of BMR. In the future, such comparisons must be done while taking the physiological state of the study animal into account.
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".