Assessment of water quality of a river using an indexing approach during the low‐flow season
Bibliographic record
Abstract
Abstract The River Chenab is one of the largest rivers in Pakistan with an average annual flow of 5.29 billion cubic metres (BCM). The river traverses a total length of 576 km through a number of densely populated and industrial cities in the Punjab province of Pakistan. In the present study, a segment of 292 km was monitored for a variety of cardinal water quality constituents during the low‐flow months of 2006–07 and 2007–08. Water quality indices (WQIs) were calculated for three uses of the river water, i.e. irrigation, drinking and aquatic life, using the CWQI 1.0 model developed by the task group of the Canadian Council of Ministers of the Environment (CCME). The results revealed that the lower river reach (185–233 km) was more polluted than the upper 185 km segment. In this river reach, overall WQI ranking was poor for drinking and marginal for both irrigation and aquatic life. The WQIs for all three uses were ranked poor at the sampling station located at 233 km along the river. Copyright © 2009 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 | 0.002 |
| Science and technology studies | 0.000 | 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".