Magnification and Toxicity of PCBs, PCDDs, and PCDFs in Upriver-Migrating Pacific Salmon
Bibliographic record
Abstract
The depletion of lipids associated with pre-spawning migration of Pacific salmon has the potential to magnify concentrations of hydrophobic organic contaminants (HOCs), which elevates risk of toxic effects. We present data from a field study of sockeye salmon (Oncorhynchus nerka) migrating to spawn in Great Central Lake, BC, which demonstrate that pre-spawning migration causes a magnification of PCB, PCDD, and PCDF concentrations in female gonads (1.9-2.5-fold), female soma (3.4-5.6-fold), and male soma (5.6-9.7-fold). We further develop a model of prespawning migration chemical magnification for sockeye salmon stocks as a function of migration distance. This model is shown to be consistent with available empirical data on pre-spawning magnification and predicts magnification factors ranging between 1.4 and 7.9 in gonad and between 1.6 and 10.4 in soma in seven Pacific salmon stocks in British Columbia. Post-migration (prespawning) toxic equivalent dioxin concentrations in roe were measured to be approximately 3 pg/g lipid in salmon from the Great Central Lake sockeye stock and estimated to range between 1.5 pg/g lipid for the shortest-migrating stocks and 7 pg/g lipid for the longest-migrating stocks. Concentrations in certain stocks approach or exceed the concentration of 3 pg/g lipid associated with 30% egg mortality in Oncorhynchus mykiss. This indicates the potential for population-level effects of current contaminant levels. It also suggests that historic contaminant concentrations, which were greater than current concentrations, may have contributed significantly to the decline of certain Pacific salmon stocks in British Columbia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".