Identification of high‐use habitat and threats to leatherback sea turtles in northern waters: new directions for conservation
Bibliographic record
Abstract
Abstract Incidental capture in fisheries threatens many marine vertebrates, however, conservation cannot be effective without identifying major sources of mortality. For the critically endangered leatherback turtle ( Dermochelys coriacea ), a reliance on fisheries observer data and an absence of behavioural data sets corresponding to a large and diverse sample of animals have focused conservation efforts on a very limited part of the species marine habitat. Using the largest satellite telemetry data set for Atlantic leatherbacks, morphometrics from foraging animals and entanglement records, we show annual return migrations to key feeding areas by males, females and juveniles, and demonstrate the importance of northern latitudes to leatherbacks. We show that leatherbacks are vulnerable to entanglement in northern coastal and shelf waters, where turtle–fishery interactions represent a greater threat to this species than previously recognized. Unless conservation efforts expand to coastal and shelf areas, present efforts alone will not be sufficient to save the species.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".