Persistent Organohalogens in Paired Fish Fillet and Eggs: Implications for Fish Consumption Advisories
Bibliographic record
Abstract
Fish consumption is associated with both health benefits from high-quality proteins, minerals, vitamins, and fatty acids and risks from contaminants in fish. Fish consumption advisories are issued by many government agencies to keep exposure to contaminants at a safe level. Such advisories are typically based on fillets and neglect consumption of other fish parts such as eggs by certain subpopulations. To evaluate potential for dietary exposure to toxic organic chemicals via fish eggs, we analyzed polybrominated diphenyl ethers (PBDEs), polychlorinated naphthalenes (PCNs), dioxin-like polychlorinated biphenyls (dlPCBs), and polychlorinated dibenzodioxins/furans (PCDD/Fs) in paired fillet and eggs of fish from a tributary to Lake Ontario, one of the North American Great Lakes. All wet weight based concentrations in fish eggs were statistically higher than in the paired fillet samples. In fish eggs, concentrations of Σ14PBDEs, Σ14PCNs, and Σ12dlPCBs were 41-118, 0.3-1.7, and 30-128 ng/g wet weight (ww), respectively; Σ3PCDD/Fs and total (dlPCB+ PCDD/Fs) toxic equivalents (TEQs) were 4-22 and 9-54 pg/g ww, respectively. In fillet samples, Σ14PBDEs, Σ14PCNs, and Σ12dlPCBs were 4-116, 0.05-0.66, and 6-85 ng/g, respectively; Σ3PCDD/Fs and TEQs were 2-10 and 3.4-31 pg/g ww, respectively. In contrast, the fillets had higher lipid normalized concentrations than the paired egg samples, suggesting that these chemicals did not reach equilibrium between the fillets and eggs. Accordingly, measured concentrations in eggs or empirical relationship with fillet rather than prediction from equilibrium partitioning model should be used to evaluate contaminant exposure via consumption of fish eggs. For fatty fish from the lower Great Lakes area, we suggest one fillet meal be reduced from the advised fish consumption frequency for consumptions of 207 ± 37, 39 ± 2, 105 ± 51, and 119 ± 9 g fish eggs of brown trout, Chinook salmon, Coho salmon, and rainbow trout, respectively.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".