Perfluoroalkyl Contaminants in Lake Ontario Lake Trout: Detailed Examination of Current Status and Long-Term Trends
Bibliographic record
Abstract
Perfluoroalkyl contaminants (PFCs) were determined in Lake Ontario Lake Trout sampled annually between 1997 and 2008 in order to assess how current trends are responding to recent regulatory bans and voluntary phase-outs. We also combined our measurements with those of a previous study to provide an updated assessment of long-term trends. Concentrations of PFCs generally increased from the late 1970s until the mid-1980s to mid-1990s, after which concentrations either remained unchanged (perfluorooctane sulfonate (PFOS) and perfluorocarboxylates) or declined (perfluorodecanesulfonate (PFDS)). The temporal trends were assessed using three models, quadratic, exponential rise to maximum, and two-segment linear piecewise function, and then evaluated for best fit using Akaike Information Criteria. For PFOS and perfluorocarboxylates, the exponential rise to maximum function had the best fit. This is particularly interesting for PFOS as it suggests that although concentrations in Lake Ontario Lake Trout may have stopped increasing in response to voluntary phase-outs in 2000-2002, declines have yet to be observed. This may be due to continuing input of PFOS from products still in use and/or slow degradation of larger precursor molecules. A power analysis of PFOS suggested that 15 years of data with a within-year sample size of 10 is required to obtain sufficient power (80%) to detect a 5% decreasing trend. However, the length of the monitoring program had a greater influence on the ability to detect a trend compared to within-year sample size. This provides evidence that additional sampling years are required to detect a response to bans and phase-outs, given the variability in the fish data. The lack of observed declines of perfluorocarboxylate residues in fish may be expected as regulations for these compounds were only recently enacted. In contrast to the other compounds, the quadratic model had the best fit for PFDS. The results of this study emphasize the importance of long-term monitoring for assessing the effectiveness of bans and phase-outs on PFCs in the environment.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".