Cyanotoxins accumulate in Lake St. Clair fish yet their fillets are safe to eat
Bibliographic record
Abstract
Abstract Consuming fish exposed to cyanobacterial harmful algal blooms (HABs) may be a major route of microcystin toxin exposure to humans. However, it remains unknown whether fish can accumulate and retain microcystins temporally in waterbodies with recurring seasonal HABs, particularly before and after a HAB event when fishing is active. We conducted a field study on Largemouth Bass, Northern Pike, Smallmouth Bass, Rock Bass, Walleye, White Bass, and Yellow Perch to assess the human health risks to microcystin toxicity via fish consumption. We collected 124 fish in 2016 and 2018 from Lake St. Clair, a large freshwater ecosystem in the North American Great Lakes that is actively fished pre- and post-HAB periods. Muscles were analyzed using the MMPB Lemieux Oxidation method for total microcystins, which was used to perform a human health risk assessment for comparison against fish consumption advisory benchmarks available for Lake St. Clair. From this collection 35 fish livers were additionally extracted to confirm the presence of microcystins. Microcystins were detected in all livers at widely varying concentrations (1-1,500 ng g -1 ww), suggesting HABs are an underappreciated and pervasive stressor to fish populations. Conversely, microcystin levels were consistently low in muscles (0-15 ng g -1 ww) and presented negligible risk, empirically supporting that fillets may be safely consumed before and after HAB events following fish consumption advisories.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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".