Seasonal diving patterns and body temperatures of juvenile green turtles at Heron Island, Australia
Bibliographic record
Abstract
This study compared diving patterns of juvenile green turtles, Chelonia mydas, in a coral reef habitat during summer and winter. Dataloggers were deployed on green turtles at Heron Island, Australia, during December 2000 and August 2001 so that dive variables and ambient water temperature (T W ) could be monitored. Cloacal temperatures (T B ) were recorded from green turtles upon capture to assess their ability to maintain a thermal gradient between T B and T W . Data show that green turtles altered diving behaviour seasonally. Green turtles spent significantly more time in shallow water (<1 m) during winter than during summer. Dive depth for dives that exceeded 1 m was 2.9 ± 0.4 m (mean ± SEM) during summer and 4.4 ± 0.6 m during winter. Dive duration in summer (13.1 ± 1.2 min) was approximately half the dive duration in winter (24.3 ± 1.6 min), and surface interval in summer (0.6 ± 0.1 min) was one-third that of the surface interval in winter (1.8 ± 0.1 min). The observed changes in behaviour may be due to seasonal changes in environmental and physiological factors. There was no statistically significant difference between T B and T W during summer or winter.
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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) | 0.000 | 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".