Cyanobacterial Neurotoxin BMAA and Mercury in Sharks
Bibliographic record
Abstract
Sharks have greater risk for bioaccumulation of marine toxins and mercury (Hg), because they are long-lived predators. Shark fins and cartilage also contain β-N-methylamino-l-alanine (BMAA), a ubiquitous cyanobacterial toxin linked to neurodegenerative diseases. Today, a significant number of shark species have found their way onto the International Union for Conservation of Nature (IUCN) Red List of Threatened Species. Many species of large sharks are threatened with extinction due in part to the growing high demand for shark fin soup and, to a lesser extent, for shark meat and cartilage products. Recent studies suggest that the consumption of shark parts may be a route to human exposure of marine toxins. Here, we investigated BMAA and Hg concentrations in fins and muscles sampled in ten species of sharks from the South Atlantic and Pacific Oceans. BMAA was detected in all shark species with only seven of the 55 samples analyzed testing below the limit of detection of the assay. Hg concentrations measured in fins and muscle samples from the 10 species ranged from 0.05 to 13.23 ng/mg. These analytical test results suggest restricting human consumption of shark meat and fins due to the high frequency and co-occurrence of two synergistic environmental neurotoxic compounds.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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 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".