Behaviour of leatherback sea turtles,<i>Dermochelys coriacea</i>, during the migratory cycle
Bibliographic record
Abstract
Leatherback sea turtles, Dermochelys coriacea, undertake broad oceanic movements. While satellite telemetry has been used to investigate the post-nesting behaviour of female turtles tagged on tropical nesting beaches, long-term behavioural patterns of turtles of different sexes and sizes have not been described. Here we investigate behaviour for 25 subadult and adult male and female turtles satellite-tagged in temperate waters off Nova Scotia, Canada. Although sex and reproductive condition contributed to variation in migratory patterns, the migratory cycle of all turtles included movement between temperate and tropical waters. Marked changes in rates of travel, and diving and surfacing behaviour, accompanied southward movement away from northern foraging areas. As turtles approached higher latitudes the following spring and summer, they assumed behaviours consistent with regular foraging activity and eventually settled in coastal areas off Canada and the northeastern USA. Behavioural patterns corresponding to various phases of the migratory cycle were consistent across multiple animals and were repeated within individuals that completed return movements to northern waters. We consider the potential biological significance of these patterns, including how turtle behaviour relates to predator avoidance, thermoregulation and prey distribution.
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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".