Quality of streams in the Red River of the North Basin, Minnesota, North Dakota, and South Dakota
Bibliographic record
Abstract
This report summarizes water-quality data from streams draining the Red River of the North Basin, which is a mostly agricultural region. It primarily has crops including small grains, corn, soybeans, sugar beets, sunflowers, and hay. The Red River drains large portions of western Minnesota and eastern North Dakota. It flows north from the United States into Canada and empties into Lake Winnipeg in Manitoba, Canada. The general quality of the waters in the Red River Basin is suitable for intended uses. Occasional exceedances of criteria or standards were brief, and many occurred before present-day wastewater-treatment methods were enacted. Concentrations of major ions, including sulfate and specific conductance, have approached and occasionally exceeded water-quality standards or criteria and may continue to do so. These exceedances likely are to be expected because of baseflow that is sustained from ground-water discharge from several aquifers, some of which are known to contain high concentrations of dissolved salts that contain sulfate and other ions. These data provide a good baseline of water quality conditions, but detections of many trace elements, including lead and mercury, may have been the result of contamination during collection and processing until methods were refined. The detections recorded in databases likely will cause concern although more recent reports show that concentrations of selected trace elements in the Red River Basin generally are low.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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".