Spatial Patterns and Temporal Trends in the Water Quality of the Tuul River in Mongolia
Bibliographic record
Abstract
The purpose of this research is to assess spatio-temporal variability of water quality determinands of the Tuul River in surrounding area of Ulaanbaatar city, Mongolia using an extensive dataset between 1998 and 2008. It presents the spatio-temporal assessment and seasonal pattern of 14 hydro-chemical determinants at 15 monitoring sites in the study area. According to the Mongolian water quality classification system, all sections of the Tuul River and its tributaries in the surrounding area of Ulaanbaatar city belong to moderately and heavily polluted waters due to high concentration of ammonium. In accordance with European Union water quality standard, the downstream section of the Tuul River fails. In order to change this situation, operation enhancement of wastewater treatment plants and artificial increment of dissolved oxygen concentration become crucial to improve the water quality significantly. Perhaps a new wastewatertreatment plant is needed for Ulaanbaatar city.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".