Predicting seasonal occurrence of leatherback turtles (<i>Dermochelys coriacea</i>) in eastern Canadian waters from turtle and ocean sunfish (<i>Mola mola</i>) sighting data and habitat characteristics
Bibliographic record
Abstract
Part of the western Atlantic population of leatherback turtles (Dermochelys coriacea (Vandelli, 1761)) forage in Canadian waters, where high-use areas have been identified using satellite telemetry and opportunistic sightings. Here, we use sightings of leatherback turtles and ocean sunfish (Mola mola (Linnaeus, 1758)) obtained during a systematic large-scale aerial survey, along with opportunistic turtle sightings, to examine the seasonal occurrence and distribution of leatherback turtles in eastern Canada. Using environmental correlates, we predict the spatial and seasonal development of potentially suitable habitats. All data sets confirmed the presence of leatherback turtles off Nova Scotia during summer. They also highlighted turtle occurrence off southern Newfoundland. Opportunistic sightings suggest a seasonal shift in main turtle concentrations from southwest to northeast, with use of southern Newfoundland waters extending into September. A generalized additive model linking environmental characteristics and turtle observations suggests adding the Grand Banks off Newfoundland and waters east of Anticosti Island in the Gulf of St. Lawrence to the potentially important habitat for leatherback turtles. Direct observations helped delineate habitat currently used by leatherback turtles. In the context of climate change, this modelling approach may improve our ability to forecast changes in turtle habitat suitability and the risks of entrapment or collision associated with potentially changing usage patterns.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".