Drinking water quality in the alpine pastures of the eastern Tibetan plateau
Bibliographic record
Abstract
The need for water quality research on the Tibetan plateau has arisen after the rangeland was allocated and leased as pasture grounds to individual nomadic families in the 1990s. These policies changed the access to water sources. The imposed fencing of the pasture tenures makes the situation even more delicate. Nomadic families are now obliged to use only water sources existing on their own site. The restrictions have caused the urge to use all available water, which resulted in increasing water quality and quantity problems. In the past, natural water sources were in common use. During the Collective era, machine-dug wells near the collective settlements facilitated the procurement of drinking water. Based on recent investigations in Dzoge county (Sichuan province), the nomadic families of some regions considered the availability of adequate drinking water for humans and animals as their biggest problem. For this study, eight water samples were collected from the Dzoge county area. All samples were from different kinds of sources, but all in continuous use by humans and animals. The samples were analyzed for typical potable water quality factors (hygienic and technique-aesthetic). The results show that the Chinese national guideline values were exceeded for NO4-N and PO4-P in most open sampling locations. Those parameters do not spoil the water by themselves, but together with suspended solids and organic materials produce a great environment for bacteria like E. coli and fecal streptococci to grow. The result analysis and pictures seen from the location reveal that bacterial growth may be the biggest problem in water quality. Even primitive protection around the water source (i.e. concrete rings, wooden barriers around edges, covers) seem to have a great impact on water quality.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".