Assessment of asbestos fiber contamination in lake sediment cores of the Thetford Mines region, southern Quebec (Canada)
Bibliographic record
Abstract
The Bécancour River in southern Quebec (Canada) has evolved under the influence of the long asbestos mining history of the Thetford Mines region (1877–2011 Common Era; CE). This river originates at the outflow of Lake Bécancour, flows through the old mining sites, and then widens to successively form Stater Pond, Trout Lake, Lake William, and Lake Joseph (25 km from the closest mine). Our objective was to assess asbestos fiber contamination in dated sediment cores retrieved at these sites by means of transmission electron microscopy. Chrysotile was the most abundant form of asbestos identified in the samples. Asbestiform actinolite and tremolite were also found. Our results revealed that precolonial sediments deposited at 4 out of the 5 study sites naturally contained asbestos fibers (up to 3.5 wt%), with mass accumulation rates historically reaching up to 1.0 mg cm−2 yr−1. However, fiber concentrations were greatly enhanced in the anthropogenic horizon of all sediment cores. The highest concentrations (up to 6.9 wt%) were found in layers from Stater Pond and Trout Lake deposited during the maximum of regional mining activities (1945‒1980 CE). Likewise, reconstructed mass accumulation rates indicated that asbestos fiber influx peaked (up to 38.6 mg cm−2 yr−1) during this epoch in all water bodies located downstream from Thetford Mines at magnitudes consistent with their proximity to the mining sites. They decreased after 1980 EC (≤ 24.4 mg cm−2 yr−1) following the decline of regional mining activities and improvement of air quality. Modern sediments of all study sites (including upstream Lake Bécancour) were nevertheless still highly enriched in asbestos fibers (up to 4.4 wt%), which can be attributed to intensive mining waste erosion in the lake catchments. Our study highlights that asbestos fiber contamination is important and widespread in the Bécancour River basin, which raises human and ecosystem health concerns.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 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".