The Influence of Warmer Temperatures Brought on by Climate Change on the Mobility of Arsenic from Lake Sediments
Bibliographic record
Abstract
Legacy arsenic contamination from past mining operations remains an environmental concern in lakes of Yellowknife (Northwest Territories) due to its post-depositional mobility.Warmer temperatures associated with climate change may impact arsenic diffusion from lake sediments either by direct effect on diffusion rate or indirect effects on microbial metabolism and sediment redox conditions.This thesis assessed the influence of warmer temperatures on arsenic diffusion from contaminated sediment of two lakes using an experimental incubation approach.Yellowknife Bay sediments (with clay, 10 % organic matter, and arsenic = 1700 µg/g) differed from sediments of Lower Martin Lake (with ~70 % organic matter and arsenic = 822 µg/g).Duplicate sediment batches from each lake were incubated for four weekly temperature treatments (5 ℃ to 20 ℃ at 5 ℃ intervals) under well-oxygenated conditions and regularly sampled for surface water chemistry.Temperature had no influence on arsenic flux from either sediment type, and other factors must be considered.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".