Assessment of Groundwater Quality in a Tidal River Basin of the Ganges Delta in Bangladesh
Bibliographic record
Abstract
At Shailmari River basin, located in the central Ganges Delta and the southwestern coastal Bangladesh, groundwater is the only potable source for water supply due to incompatible surface water sources. However, salinity degradation along with arsenic and iron contamination poses a serious health threat to the basin community. Considering this, an investigation was carried out along both banks of the river to assess groundwater vulnerability and its quality for drinking by conducting multi-seasonal water sampling campaigns from 20 domestic wells and analyses (both in-situ and laboratory) for several physico-chemical (pH, EC, TDS and major ions) and biological (coliforms) parameters. The results show slightly alkaline groundwater in the study area with largely variable chemical composition, i.e. EC varies from around 1900 to 2700 μS/cm. The abundance of major ions indicates as Na+ > Ca2+ > Mg2+ > K+ for cations and > Cl- > > > for anions. As per the Canadian water quality index (CCMEWQI), almost all groundwater samples concentrate in the marginal category meaning that groundwater is frequently threatened. Besides, it is not fully safe for drinking as revealed from comparison of geochemical data with national and WHO water quality standards.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| 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".