Evaluation of thermotolerant coliforms and salinity in the four available water sources of an irrigated region of southern Sri Lanka
Bibliographic record
Abstract
Abstract In many developing countries a close linkage exists between drinking and irrigation water; however, the effects of irrigation management on drinking water availability and quality, and what drinking water supplies are best suited to irrigated areas, have been little studied. Bacterial contamination and salinity of drinking water sources in a community within the Uda Walawe irrigation system of southern Sri Lanka were monitored from August to December 2000. Water with the lowest combination of faecal contamination and salt content (highest quality) was found in shallow wells, recharged with seepage water from the irrigation system. Of these wells, those surrounded by a protective wall had the lowest levels of thermotolerant coliforms (median of 244 ThCU 100 ml−1) as compared to shallow wells without protective walls (549 ThCU 100 ml−1). Furthermore, tube well waters were highly saline (average of 0.67 mS cm−1), while canal and reservoir waters had high thermotolerant coliform levels (3940 and 950 ThCU 100 ml−1). Interseasonal canal closures eliminate the canals as a water source, lowering water levels in shallow wells, and thus reducing regional water availability. Concrete lining of canals may exacerbate the drying up of shallow wells during canal closure, therefore eliminating the primary source of water in the region that can be used for drinking after only simple treatment. Copyright © 2002 John Wiley & Sons, Ltd.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".