Fish Exhibit Distinct Fluorochemical and δ15N Isotopic Signatures in the St. Lawrence River Impacted by Municipal Wastewater Effluents
Bibliographic record
Abstract
We examined the influence of Montreal wastewater treatment plant (WWTP) effluents on two top predators, Walleye (Sander vitreus) and Sauger (Sander canadensis), with a focus on δ15N isotopic signatures and per- and polyfluoroalkyl substances (PFAS). These two fish species were collected in the summer 2013 in the St. Lawrence River upstream and downstream from a major WWTP, as well as in background sites (semi-remote lakes). Most of the δ15N variations for Sauger and Walleye are attributable to 1) δ15N values of the primary producers and sewage-derived particulate organic matter (SDPOM) at the base of the trophic food chain, 2) agricultural activities combined with biogeochemical processes, and 3) food web length. δ15N was significantly lower in fish collected in the effluent-mixed water masses than other sites of the St. Lawrence River, attributed to the SDPOM of the WWTP effluent. Relative to the background sites, certain PFAS were present at much higher levels in the St. Lawrence River, with profiles dominated by perfluoroalkyl sulfonates (PFSA). However, PFSA profiles generally remained consistent along the St. Lawrence River. PFOS levels in fish from the St. Lawrence exceeded the current Federal Environmental Quality Guidelines for protecting piscivorous mammals or birds. However, the human chronic daily intake of PFOS remained below current thresholds suggested by national agencies.
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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".