Distribution, Drivers, and Threats of Aluminum in Groundwater in Nova Scotia, Canada
Bibliographic record
Abstract
Increased rates of acid deposition derived from the burning of fossil fuels over the last century have resulted in the acidification and increase in aluminum (Al) levels in freshwaters and soils in sensitive areas. While the acidification of surface waters such as lakes and rivers has been extensively studied, the acidification status and resulting Al concentrations in groundwater are poorly understood. Here we aim to describe the distribution of Al in groundwater across the province of Nova Scotia, Canada. We investigate the hydrogeological conditions that influence Al concentrations in groundwater and compare Al concentrations to legislated threshold levels for human and aquatic health. We found groundwater Al concentrations to be highest in areas underlain by plutonic and metamorphic bedrock types as well as surficial aquifers, with pH and organic carbon concentrations having the strongest correlation with groundwater Al concentrations. Few samples exceed the maximum acceptable concentration of 2900 µg/L released by Health Canada (2021), but these exceedances are important to highlight given the challenges with respect to Al treatment in private domestic wells and our evolving understanding of Al impacts to human health. High concentrations of Al in groundwater may also be exported to surface waters such as rivers and lakes, where they can be harmful to aquatic populations such as Atlantic salmon (Salmo salar). We recommend that private well owners test their water supplies for Al, and that further studies on Al export from groundwater to surface water be carried out in the most high-risk areas coincident with important Atlantic salmon river watersheds.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 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".