Bioaccumulation of pharmaceuticals and personal care product chemicals in fish exposed to wastewater effluent in an urban wetland
Bibliographic record
Abstract
Abstract The bioaccumulation of a broad range of pharmaceuticals and personal care product chemicals (PPCPs) was studied in Cootes Paradise Marsh (CPM), an urban wetland that receives tertiary treated municipal waste waters as well as urban storm runoff. We measured PPCPs in caged and wild goldfish, as well as wild carp, and compared observed bioaccumulation factors (BAFP) using concentrations in surface waters and fish blood plasma, with modeled BAFs. Thirty-two PPCPs were detected in water from the central CPM site (CPM3) while 64 PPCPs were found at higher concentrations at a site immediately downstream of the effluent outflow (CPM1). Following a 3-week deployment, 15 PPCPs were detected in the plasma of caged goldfish at CPM1, and 14 at CPM3, compared to only 3 in goldfish caged at a reference site. The highest BAFP in goldfish were for the antidepressant Σfluoxetine averaging 386 L/kg in caged and 906 L/kg in wild goldfish, respectively. In carp, ΣDiazepam (diazepam and oxazepam) had the highest BAFP (927 L/kg). This study identified a broader range of PPCPs in fish and surface waters than previously reported. However, modeled BAFs did not show good agreement with observed whole body or plasma BAFs, demonstrating that more work is needed to better explain bioaccumulation of PPCPs.
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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 | 0.000 | 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) | 0.000 | 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".