Natural and Anthropogenic Gadolinium in Natural Water Systems in the Columbus, OH and Rochester, NY Areas
Bibliographic record
Abstract
Gadolinium (Gd) chelates used to enhance contrast in Magnetic Resonant Imaging (MRI) are the most common source of anthropogenic Gd in water systems and humans. Most of the ~1 g of Gd injected is excreted in urine and likely enters water systems through wastewater treatment plants (WWTPs). Anthropogenic Gd concentrations in water samples from the Scioto Valley Watershed in the Columbus, OH area ranged from 8 parts per trillion (ppt (ng/L)) upstream of WWTPs to 78 ppt directly downstream of WWTPs consistent with anthropogenic Gd being added to the rivers from WWTPs. Although most of the Gd injected for a contrast enhanced MRI is excreted in urine, a small fraction of the Gd can be retained in the body for years. Furthermore, there is some evidence that a small percentage of humans that have no medical history of a Gd chelate-enhanced contrast MRI have slightly elevated Gd in body tissues (e.g. placentas, bones). A possible source this anthropogenic Gd could be anthropogenic Gd in drinking water. Municipal drinking water for the Rochester, NY, area comes from Hemlock Lake, Lake Ontario, or a mixture of the two. WWTP effluent flows into Lake Ontario but not into Hemlock Lake. Municipal drinking water samples from locations served by the different sources were collected. Anthropogenic Gd concentrations in the drinking water ranged from 0.5 to 2.7 ppt. Water samples were also collected from Hemlock Lake (2 locations) and from Lake Ontario (4 locations). The natural concentrations of rare earth elements (REEs) in these samples were much larger (5.2 to 17 ppt) than the natural concentrations of REEs in the drinking water samples (0.9 to 3.5 ppt) or the river system samples from the Columbus, OH area (4 to 14 ppt).
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".