Seasonal metabolism of juvenile green turtles (<i>Chelonia mydas</i>) at Heron Island, Australia
Bibliographic record
Abstract
We investigated seasonal changes in the energetics of juvenile green turtles (Chelonia mydas (L., 1758)) (9.8–23.8 kg) from a resident population on the southern Great Barrier Reef. Doubly labeled water was used to determine water flux and field metabolic rate (FMR) of green turtles during summer (mean water temperature (TW) = 25.8 °C) and winter (mean TW = 21.4 °C), and muscle tissue was collected for analysis of thermal sensitivity of metabolic enzyme activity. There was no significant seasonal difference in total body water (TBW) content (73.7% and 75.1% of body mass in summer and winter, respectively) or water flux (7.5% and 6.1% of TBW per day in summer and winter, respectively). The mean FMR during winter (81 ± 15 kJ·kg–1·d–1) was 43% lower than that during summer (142 ± 33 kJ·kg–1·d–1), but the seasonal difference in FMR marginally failed to reach statistical significance (P = 0.17). Thermal dependence of citrate synthase, lactate dehydrogenase, and pyruvate kinase activity was relatively low (Q10 = 1.20–1.68) over the range of temperatures experienced by turtles during summer and winter, and there were no significant seasonal differences in enzyme activity. In summary, juvenile green turtles experience only moderate changes in metabolism within the temperature range and environmental conditions experienced seasonally at this subtropical site.
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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".