Ontogeny and ecological significance of metabolic rates in sea turtle hatchlings
Bibliographic record
Abstract
BACKGROUND: Sea turtle hatchlings must avoid numerous predators during dispersal from their nesting beaches to foraging grounds. Hatchlings minimise time spent in predator-dense neritic waters by swimming almost continuously for approximately the first 24 h post-emergence, termed the 'frenzy'. Post-frenzy, hatchling activity gradually declines as they swim in less predator-dense pelagic waters. It is well documented that hatchlings exhibit elevated metabolic rates during the frenzy to power their almost continuous swimming, but studies on post-frenzy MRs are sparse. RESULTS: We measured the frenzy and post-frenzy oxygen consumption of hatchlings of five species of sea turtle at different activity levels and ages to compare the ontogeny of mass-specific hatchling metabolic rates. Maximal metabolic rates were always higher than resting metabolic rates, but metabolic rates during routine swimming resembled resting metabolic rates in leatherback turtle hatchlings during the frenzy and post-frenzy, and in loggerhead hatchlings during the post-frenzy. Crawling metabolic rates did not differ among species, but green turtles had the highest metabolic rates during frenzy and post-frenzy swimming. CONCLUSIONS: Differences in metabolic rate reflect the varying dispersal stratagems of each species and have important implications for dispersal ability, yolk consumption and survival. Our results provide the foundations for links between the physiology and ecology of dispersal of sea turtles.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".