Concentrations of per- and polyfluoroalkyl substances in Canadian sea otters ( <i>Enhydra lutris</i> ) are higher near urban centers
Bibliographic record
Abstract
Per- and polyfluoroalkyl substances (PFAS) are thousands of toxic synthetic chemicals that bioaccumulate and persist in the environment. They are known to cause immunotoxicity, organ damage, endocrine disruption, and reproductive impairments in wildlife such as sea otters (Enhydra lutris). However, there is limited information on the distribution of these chemicals across the northeastern Pacific, and baseline data are missing to assess their potential impacts on sea otters in regions such as British Columbia (BC), Canada. We analyzed liver (n = 11) and skeletal muscle samples (n = 5) from 11 deceased sea otters from coastal BC using the U.S. Environmental Protection Agency method 1633 with ultrahigh performance liquid chromatography coupled to a triple quadrupole mass spectrometer. We found 8 of the 40 tested PFAS were present in all sampled sea otters, although concentrations of each PFAS varied between individuals. Sea otter livers contained more PFAS compounds at higher total average concentrations than skeletal muscle (i.e., 8 PFAS totaling 10.38 ng/g wet wt vs. 1 PFAS totaling 0.38 ng/g wet wt). Only perfluorooctanesulfonamide (PFOSA) was identified in both liver and muscle tissues, whereas the remaining 7 PFAS were unique to the liver. The three PFAS that dominated the liver PFAS composition (perfluorononanoic acid, PFOSA, and perfluorooctanesulfonic acid) accounted for 84% of the contaminant load in the livers. Geographically, PFAS concentrations were more than three times higher on average in sea otters recovered near major cities and shipping routes. Identifying the contaminants accumulating in sea otters provides insights into the health threats confronted by recovering sea otter populations. Our study also establishes baseline PFAS contamination levels in BC sea otters, which can be used to monitor and regulate the presence of PFAS on marine environments in western Canada.
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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 | 0.001 | 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".