Spatial Distribution of Perfluoroalkyl Contaminants in Lake Trout from the Great Lakes
Bibliographic record
Abstract
Individual whole body homogenates of 4 year old lake trout (Salvelinus namaycush) samples collected in 2001 from each of the Great Lakes were extracted using a novel fluorophilicity cleanup step and analyzed for perfluoroalkyl compounds (PFCs). Standard addition and internal standardization were used for quantification. Results were reported (+/- SE) for perfluorinated carboxylates (PFCAs), perfluorinated sulfonates (PFSAs), and unsaturated fluorotelomer carboxylates (8:2 and 10:2 FTUCA). The lowest average concentration of sigmaPFC was found in samples from Lake Superior (13+/-1 ng g(-1)), while the highest average concentration was found in samples from Lake Erie (152+/-14 ng g(-1)). Samples from Lake Ontario (60+/-5 ng g(-1)) and Lake Huron (58 +/-10 ng g(-1)) showed similar average sigmaPFC concentrations, although the perfluorinated sulfonate/carboxylate ratios were different. The major perfluoroalkyl contaminant observed was perfluorooctane sulfonate (PFOS) with the highest concentration found in samples from Lake Erie (121+/-14 ng g(-1)), followed by samples from Lake Ontario (46+/-5 ng g(-1)), Lake Huron (39 +/-10 ng g(-1)), Lake Michigan (16+/-3 ng g(-1)), and Lake Superior (5+/-1 ng g(-1)). Perfluorodecane sulfonate (PFDS) was detected in 89% of the samples, with the highest concentration in Lake Erie samples (9.8+/-1.6 ng g(-1)), and lowest concentration in samples from Lake Superior (0.7 +/- 0.1 ng g(-1)). Statistically significant correlations were observed between PFOS and PFDS concentrations, and PFOS concentration and body weight, respectively. The PFCAs were detected in all samples, with the highest total average concentration in samples from Lake Erie (19 ng g(-1)), followed by samples from Lake Huron (16 ng g(-1)), Lake Ontario (10 ng g(-1)), Lake Michigan (9 ng g(-1)) and Lake Superior (7 ng g(-1)). The compounds with significant contributions to the sigmaPFCA concentrations were PFOA and C9-C13-PFCAs. The 8:2 FTUCA was detected at concentrations ranging between 0.1 and 0.2 ng g-1, with the highest level in samples showing also elevated concentrations of PFOA (4.4 ng g(-1) for Lake Michigan vs 1.5 ng g(-1) for all other samples). The 10:2 FTUCA was detected only in 9% of all samples (nd, 45 pg g(-1)). For those PFCs where we determined lake water concentrations, the highest log BAFs were calculated for PFOS (4.1), PFDA (3.9), and PFOSA (3.8).
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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 | 0.000 | 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".