Cumulative effects of the transport of asbestos-rich serpentine sediments in the trans-boundary Sumas Watershed in Washington State and British Columbia
Bibliographic record
Abstract
Serpentinitic sediments rich in chrysotile asbestos, from a natural landslide in the Sumas River Watershed in Washington State, are deposited on agricultural land during flooding events, creating a health concern for the rural population. The sediments have a chemical composition of high magnesium (Mg), nickel (Ni) and chromium (Cr) and high pH values compared with non-serpentinitic sediments that originate from the agricultural lowland. As the sediments are transported from the headwater to the mouth, the effects of mixing with non-serpentinitic water from agricultural drainage decrease the pH, increase the contents of organic matter, nitrate and zinc (Zn), and impact the sediments that originated from the landslide. A comparison of bed and suspended sediment showed that there is a clear seasonal effect with lower Mg and Ni values during low flow for both types of sediments. Bed sediments were consistently higher than suspended sediment in Mg and Ni. Sediments emerging from the landslide have positive zeta potentials but disperse very rapidly and become negatively charged. Once the sediment interacts with agricultural sources downstream the zeta potential becomes more negative, causing the sediment to stay suspended. It is postulated that at high pH, Mg is leached from the brucite layer of chrysotile and precipitates as Mg carbonate, which enriches the bed sediments in Mg and associated trace metal concentration.
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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 | 0.001 |
| 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 | 0.002 | 0.000 |
| Open science | 0.001 | 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".