An assessment of uranium in groundwater in the Grand Canyon region
Bibliographic record
Abstract
Abstract The Grand Canyon region in northern Arizona is a home or sacred place of origin for many Native Americans and is visited by over 6 million tourists each year. Most communities in the area depend upon groundwater for all water uses. Some of the highest-grade uranium ore in the United States also is found in the Grand Canyon region. A withdrawal of over 4000 km 2 of Federal land in the Grand Canyon region from new uranium mining activities for 20 years was instituted in 2012, owing in part to a lack of scientific data on potential effects from uranium mining on water resources in the area. The U.S. Geological Survey has collected groundwater chemistry samples since 1981 in the Grand Canyon region to better understand the current state of groundwater quality, to monitor for changes in groundwater quality that may be the result of mining activities, and to identify "hot spots" with elevated metal concentrations and investigate the causes. This manuscript presents results for the assessment of uranium in groundwater in the Grand Canyon region. Analytical results for uranium in groundwater in the Grand Canyon region were available for 573 samples collected from 180 spring sites and 26 wells from September 1, 1981 to October 7, 2020. Samples were collected from springs issuing from stratigraphic units above, within, and below the Permian strata that host uranium ore in breccia pipes in the area. Maximum uranium concentrations at groundwater sites in the region ranged from less than 1 µg/L at 23 sites (11%) to 100 µg/L or more at 4 sites (2%). Of the 206 groundwater sites sampled, 195 sites (95%) had maximum observed uranium concentrations less than the U.S. Environmental Protection Agency’s Maximum Contaminant Level of 30 µg/L for drinking water and 177 sites (86%) had uranium concentrations less than the 15 µg/L Canadian benchmark for protection of aquatic life in freshwater. The establishment of baseline groundwater quality is an important first step in monitoring for change in water chemistry throughout mining lifecycles and beyond to ensure the health of these critical groundwater resources.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 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 teacher head, 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".