Geochemical controls on uranium and arsenic in Yukon groundwater
Bibliographic record
Abstract
Uranium and arsenic are naturally occurring metal(loid)s that pose a threat to groundwater security on a global scale. The Yukon is a territory in the subarctic Canadian Cordillera, where 97% of inhabitants rely on groundwater for drinking water and domestic use. The climate of the Yukon is warming at nearly four times faster than the global average, and permafrost thaw and changing precipitation patterns threaten the safety of groundwater. The purpose of this research is to investigate the spatial distribution and sources of geogenic uranium and arsenic in Yukon groundwaters, determine the geochemical mechanisms that control the mobility of uranium and arsenic, and assess potential impacts of climate change on uranium and arsenic mobility. 129 wells across the Yukon were sampled and analyzed. Uranium concentrations greater than half the Maximum Acceptable Concentration (MAC) were found primarily in felsic-intermediate and high-grade metamorphic fractured bedrock aquifers near sulphide-mineral ores, and overlying unconsolidated sediment aquifers. The formation of stable calcium-carbonato-uranyl complexes in primarily oxidizing groundwaters controlled the mobility of uranium. Arsenic concentrations greater than half the MAC were found in unconsolidated aquifers and in association with sulphide-mineral ores in fractured bedrock aquifers. Reductive dissolution of iron-(oxyhydr)oxides and competition with carbonate for sorption sites influenced arsenic concentrations. Sulphide-mineral oxidation was an additional control on arsenic mobility in fractured bedrock aquifers. Arsenic and uranium frequently co-occurred in samples from wells in fractured bedrock aquifers despite their differing redox geochemistry, likely due to wells drawing from multiple discrete fractures during sampling and their shared association with sulphide-mineral oxidation. Projected permafrost thaw will change hydrology and geochemistry of Yukon groundwaters, with uncertain outcomes for arsenic and uranium mobility.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".