Assessment of Groundwater Quality at Selected Location of three Wells and Al-Warrar Canal, Ramadi City, Iraq.
Bibliographic record
Abstract
To classification groundwater quality in the study area, three wells were drilled at a depth of 10m and selected two locations across Al Warrar Canal to represent their water quality. Water samples were collected from these wells and the Warrar Canal to examine water quality. Then results were compared against the World Health Organization (WHO) limits to study the Index of Water Quality (WQI). WQI was calculated according to the Canadian Council of Ministers of the Environment (CCME), and the quality of water was evaluated for domestic and irrigation uses. The samples were tested for electrical conductivity, pH, temperature, total dissolved solids, chloride, total hardness, nitrate, and alkalinity according to the standard methods. The results of laboratory analysis showed significant differences among the wells and Warrar Canal water quality in the measured parameters according to WHO limits. Due to many human activities like urbanization, agrarian overflow, drainage of untreated sewage, and industrialization, high values of trace elements and heavy metals were recorded in wells three. For agriculture purposes, the results show that the water in the three wells is very high salinity, where the Warrar Canal is high salinity, and Canal water causes saline and alkali damages. It was recommended that the WQI in three wells was poor water quality whereas, marginal water quality was pointed in AL Warrar Canal.
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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 | 0.001 | 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".