A comparison of the physiological responses, behaviour and biotransformation of paralytic shellfish poisoning toxins in a surf-clam (Paphies donacina) and the green-lipped mussel (Perna canaliculus)
Bibliographic record
Abstract
The accumulation of paralytic shellfish toxins (PSTs) in bivalves is species specific. We compared the physiological responses and the toxin profiles in tissues of the burrowing surf clam, Paphies donacina, and the green-lipped mussel, Perna canaliculus, exposed to the toxic dinoflagellate Alexandrium tamarense. Bivalves were supplied with the toxic algae for 10 days, then allowed a detoxification period of 8 days. Clearance rates of mussels and clams were similar when fed either with toxic A. tamarense or non-toxic A. margalefi. Byssus production in the mussel was inhibited and exhalent siphon activity in clams was erratic following exposure to A. tamarense. There were considerable differences in the toxic profile between the dinoflagellate A. tamarense, and tissues of the mussel and the surf clam, indicating that bioconversion of the PSTs had taken place. Toxin profiles of the tissues were both species and tissue specific. Following an 8-day detoxification period, total PSTs in mussels had fallen to safe concentrations below 50 µg per 100 g, whereas concentrations in clams remained high, with an average value greater than 600 µg STX di-HCL equivalents per 100 g. The results confirmed that mussels and clams are important monitoring organisms for toxic algal blooms and can be used to minimise the health risk of PSTs to humans.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".