Selective\nUptake and Bioaccumulation of Antidepressants in Fish from Effluent-Impacted\nNiagara River
Bibliographic record
Abstract
The\ncontinuous release of pharmaceuticals and personal care products (PPCPs)\ninto freshwater systems impacts the health of aquatic organisms. This\nstudy evaluates the concentrations and bioaccumulation of PPCPs and\nthe selective uptake of antidepressants in fish from the Niagara River,\nwhich connects two of the North American Great lakes (Erie and Ontario).\nThe Niagara River receives PPCPs from different wastewater treatment\nplants (WWTPs) situated along the river and Lake Erie. Of the 22 targeted\nPPCPs, 11 were found at part-per-billion levels in WWTP effluents\nand at part-per-trillion levels in river water samples. The major\npollutants observed were the antidepressants (citalopram, paroxetine,\nsertraline, venlafaxine, and bupropion, and their metabolites norfluoxetine\nand norsertraline) and the antihistamine diphenhydramine. These PPCPs\naccumulate in various fish organs, with norsertraline exhibiting the\nhighest bioaccumulation factor (up to about 3000) in the liver of\nrudd (<i>Scardinius erythrophthalmus</i>), which is an invasive\nspecies to the Great Lakes. The antidepressants were selectively taken\nup by various fish species at different trophic levels, and were further\nmetabolized once inside the organism. The highest bioaccumulation\nwas found in the brain, followed by liver, muscle, and gonads, and\ncan be attributed to direct exposure to WWTP effluent.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.006 | 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 teacher head, 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".