Behavioral and metabolic contributions to thermoregulation in freely swimming leatherback turtles at high latitudes
Bibliographic record
Abstract
Leatherback turtles in the Northwest Atlantic Ocean have a broad geographic range that extends from nesting beaches near the equator to seasonal foraging grounds as far north as Canada. The ability of leatherbacks to maintain core body temperature (Tb) higher than that of the surrounding water is thought to be a key element of their biology that permits them to exploit productive waters at high latitudes. We provide the first recordings of Tb from freely swimming leatherbacks at a northern foraging ground, and use these data to assess the importance of behavioral adjustments and metabolic sources of heat for maintenance of the thermal gradient (Tg). The mean Tb for individual leatherbacks ranged from 25.4 ± 1.7 to 27.3 ± 0.3 °C, and Tg ranged from 10.7 ± 2.4 to 12.1 ± 1.7 °C. Variation in mean Tb was best explained by the amount of time that turtles spent in the relatively warm surface waters. A diel trend in Tb was apparent, with daytime cooling suggestive of prey ingestion and night-time warming attributable to endogenous heat production. We estimate that metabolic rates necessary to support the observed Tg are ~3 times higher than resting metabolic rate, and that specific dynamic action is an important source of heat for foraging leatherbacks.
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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 | 0.000 | 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".