Microlitter in the water, sediments, and mussels of the Saint John River (Wolastoq) watershed, Atlantic Canada
Bibliographic record
Abstract
Microlitter is a widespread contaminant with implications for aquatic health; however, knowledge of its distribution in fresh waters is limited. We examined microlitter in surface water, sediment, and mussels within the Saint John River and four major tributaries. Microlitter was present at all 89 sites, with concentrations in water equivalent to other Canadian watersheds. Microlitter concentrations likely reflected differences in land use and development. Comparisons between rivers generally revealed distinct water microlitter particle compositions, suggesting that input sources were specific to each river, while microlitter in sediments and mussels was largely homogeneous among rivers. There was little similarity in concentration and composition of microlitter among the three matrices sampled. Microlitter in sediments and mussels may not reliably track concentration and composition in aquatic environments. Microlitter concentration was not significantly greater downstream of wastewater treatment plants. Airborne microlitter transportation was evident, as remote sites in two tributary rivers demonstrated the highest concentrations of microlitter. Our data highlights the prevalence of microlitter in rural rivers, underscoring the ubiquity of this emerging contaminant and its integration into food webs.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".