Ecological roles and importance of sharks in the Anthropocene Ocean
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In ecosystems, sharks can be predators, competitors, facilitators, nutrient transporters, and food. However, overfishing and other threats have greatly reduced shark populations, altering their roles and effects on ecosystems. We review these changes and implications for ecosystem function and management. Macropredatory sharks are often disproportionately affected by humans but can influence prey and coastal ecosystems, including facilitating carbon sequestration. Like terrestrial predators, sharks may be crucial to ecosystem functioning under climate change. However, large ecosystem effects of sharks are not ubiquitous. Increasing human uses of oceans are changing shark roles, necessitating management consideration. Rebuilding key populations and incorporating shark ecological roles, including less obvious ones, into management efforts are critical for retaining sharks' functional value. Coupled social-ecological frameworks can facilitate these efforts.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 it