Ecological erosion and expanding extinction risk of sharks and rays
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
The true state of ocean biodiversity is difficult to assess, and there are few global indicators to track the primary threat of overfishing. We calculated a 50-year Red List Index of extinction risk and ecological function for 1199 sharks and rays and found that since 1970, overfishing has halved their populations and their Red List Index has worsened by 19%. Overfishing the largest species in nearshore and pelagic habitats risks loss of ecomorphotypes and a 5 to 22% erosion of functional diversity. Extinction risk is higher in countries with large human coastal populations but lower in nations with stronger governance, larger economies, and greater beneficial fisheries subsidies. Restricting fishing (including incidental catch) and trade to sustainable levels combined with prohibiting retention of highly threatened species can avert further depletion, widespread loss of population connectivity, and top-down predator control.
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.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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