Municipal Tap Water in the Urban Drinking Water Monitoring Pilots in Sichuan
Bibliographic record
Abstract
Objective To provide evidence for improving the safety of drinking water by carring out monitoring network pilot of urban drinking water and understanding the hygienic status of the water.Methods The samples of municipal tap water were collected in 5 different grade cities,the monitoring data of the samples were evaluated and analyzed.Results The qualified rate of municipal tap water in experimental areas was 93.3% from July,2009 to June,2010.The qualified rate of individual indices was high,most indices qualified rate was above 99%.The qualified rate of general chemical indices was higher than sensory characteristical indices,microbial indices and disinfectant indices.The tap water of prefectural-level city had the highest qualified rate,the provincial capital city was lower,the lowest qualified rate of tap water was in county-level cities.The qualified rate of tap water in the third quarter of 2009 was lower than other three quarters.All the differences had statistical significance.Conclusion The qualified rate of municipal tap water in experimental areas is high,but most of the indices have substandard conditions in different degree.There is a certain degree of risk in drinking water,that should be paid attention.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".