Hidden Diversity of Threatened Sharks and Rays in the Global Meat Trade
Bibliographic record
Abstract
International wildlife trade is a major source of biodiversity loss, yet many species lie hidden within aggregated data that conceals trade impacts. We overcome this problem for the largest vertebrate wildlife trade globally – shark and ray meat – comprising 438 538 mt yr -1 across more than 150 species, 76% of which are Threatened. Revealed trade contains greater quantities of skates (+10%), hammerheads (+8%), and smoothhounds, dogfishes & tope (+5%), and fewer pelagic sharks (-38%) than previously known. Shorttail yellownose skate, smoothound, silky, mako, and blue sharks are the most underreported meat species, due to aggregated landings from China, Argentina, Japan, and Indonesia, demonstrating international trade in shark and ray meat as a diverse, pervasive, and previously hidden source of fishing mortality for many threatened species.
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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 | 0.000 | 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 | 0.001 | 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 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".