You can swim but you can't hide: the global status and conservation of oceanic pelagic sharks and rays
Bibliographic record
Abstract
1. Fishing spans all oceans and the impact on ocean predators such as sharks and rays is largely unknown. A lack of data and complicated jurisdictional issues present particular challenges for assessing and conserving high seas biodiversity. It is clear, however, that pelagic sharks and rays of the open ocean are subject to high and often unrestricted levels of mortality from bycatch and targeted fisheries for their meat and valuable fins. 2. These species exhibit a wide range of life-history characteristics, but many have relatively low productivity and consequently relatively high intrinsic vulnerability to over-exploitation. The IUCN — World Conservation Union Red List criteria were used to assess the global status of 21 oceanic pelagic shark and ray species. 3. Three-quarters (16) of these species are classified as Threatened or Near Threatened. Eleven species are globally threatened with higher risk of extinction: the giant devilray is Endangered, ten sharks are Vulnerable and a further five species are Near Threatened. Threat status depends on the interaction between the demographic resilience of the species and intensity of fisheries exploitation. 4. 4. Most threatened species, like the shortfin mako shark, have low population increase rates and suffer high fishing mortality throughout their range. Species with a lower risk of extinction have either fast, resilient life histories (e.g. pelagic stingray) or are species with slow, less resilient life histories but subject to fisheries management (e.g. salmon shark). 5. 5. Recommendations, including implementing and enforcing finning bans and catch limits, are made to guide effective conservation and management of these sharks and rays. Copyright © 2008 John Wiley & Sons, Ltd.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".