Acoustic monitoring of sixgill shark movements in Puget Sound: evidence for localized movement
Bibliographic record
Abstract
Understanding the movements of species, particularly those that may exert strong influence on community structure or that may be susceptible to human perturbations, is critical to effectively conserve and manage populations. However, the study of movement behavior in marine fishes has been historically difficult and typically produces a limited amount of data (i.e., start and end points). We use an array of automated acoustic receivers to monitor autumn and winter movement patterns of sixgill sharks ( Hexanchus griseus (Bonnaterre, 1788)) in Puget Sound, Washington, USA. Daily movement of sharks and maximum distance moved from tagging sites varied with size, with larger sharks having shorter daily movements and maximum distances from tagging locations than smaller sharks. Sharks were detected at the same site as the previous day 76% of the time. Movement away from the shark’s tagging location increased slightly over the duration of the study, but most sharks occupied the same sites for most of the study. These relatively small and stable movement patterns could lead to localized, top-down impacts from sixgill sharks and suggest that local human perturbations, such as fishing or pollution, have the potential to negatively affect local populations of sixgill sharks.
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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 | 0.001 | 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 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".