Results Analysis on Microbial Detection of Drinking Water in Shenyang Railway Area
Bibliographic record
Abstract
[Objective]To learn the sanitary condition of drinking water in all stations and depots of Shenyang railway area,so as to ensure the drinking water safety of railway workers.[Methods]The microbial detection was conducted in 338 water samples.[Results]The total qualified rate was 90.8%,the qualified rate of total bacteria counts was 90.8%,and that of total coliform group and thermotolerant coliform bacteria was 93.5%.The quality of drinking water in first and fourth quarter was better than that in second and third quarter.There was significant difference in qualified rates of all water samples between the secondary pressure water and finished water(χ2=5.82,P0.05),and the difference between the finished water and dispersed supply water was significant(χ2=5.57,P0.05).[Conclusion]The pollution of drinking water in this area is severe,especially dispersed water supply.The drinking water safety of railway workers needs to be solved urgently.
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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 | 0.000 | 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) | 0.001 | 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".