Emergent research and priorities for shark and ray conservation
Bibliographic record
Abstract
Over the past 4 decades there has been a growing concern for the conservation status of elasmobranchs (sharks and rays). In 2002, the first elasmobranch species were added to Appendix II of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). Less than 20 yr later, there were 39 species on Appendix II and 5 on Appendix I. Despite growing concern, effective conservation and management remain challenged by a lack of data on population status for many species, human−wildlife interactions, threats to population viability, and the efficacy of conservation approaches. We surveyed 100 of the most frequently published and cited experts on elasmobranchs and, based on ranked responses, prioritized 20 research questions on elasmobranch conservation. To address these questions, we then convened a group of 47 experts from 35 institutions and 12 countries. The 20 questions were organized into the following broad categories: (1) status and threats, (2) population and ecology, and (3) conservation and management. For each section, we sought to synthesize existing knowledge, describe consensus or diverging views, identify gaps, and suggest promising future directions and research priorities. The resulting synthesis aggregates an array of perspectives on emergent research and priority directions for elasmobranch conservation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.041 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".