First insights into the fine-scale vertical movements of a Carolina hammerhead, Sphyrna gilberti, and a hybrid between Carolina and scalloped hammerhead
Bibliographic record
Abstract
Satellite telemetry has enabled the tracking of marine predators’ vertical and horizontal habitat use and migration patterns. These insights provide valuable information that inform management and conservation of threatened species. In this study, a scalloped hammerhead, Sphyrna lewini, (125 cm FL; immature female) a Carolina hammerhead, Sphyrna gilberti, (138 cm FL; immature female) and a scalloped/Carolina hammerhead hybrid (160 cm FL; immature male) were tagged with PSATLIFE’s off the coast of North Carolina. Tag data revealed that the Carolina hammerhead exploited a wide depth range, with a maximum depth of 846 m. Dive patterns of the scalloped hammerhead revealed differences in vertical space use, with the scalloped hammerhead primarily remaining within the top 200 m of the water column, and with a maximum depth of 380 m. The hybrid individual demonstrated similar dive patterns to those of the scalloped hammerhead, with a maximum depth of 203 m. This study presents the first vertical movement data for Carolina and hybrid scalloped/Carolina hammerheads, offering new insights into interspecific variation in depth use. Future research should explore if there are differences in habitat use and foraging strategies, as they may serve as distinguishing characteristics and support the development of effective management measures.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".