Assessment of water quality using Canadian Water Quality Index and GIS in Himreen Dam Lake, Iraq
Bibliographic record
Abstract
The Canadian versions of Water Quality Index (WQI) and Geographical Information Systems (GIS) were applied in this study to assess the water quality of Himreen Dam Lake. Water samples were taken seasonally during the period from summer 2014 to spring 2015. A total of 10 parameters were measured in this work, and were considered in calculating the water quality index (WQI), namely: potential hydrogen ion (pH), electrical conductivity (EC), total dissolved solid (TDS), sodium (Na+), calcium (Ca+2), magnesium (Mg+2), chloride (Cl-), sulphate (SO4-2), nitrate (NO3) and sodium adsorption ratio (SAR). The results showed that the pH was ranged from 7.1-7.9, EC was varied from 558-864 µS/cm and TDS was ranged between 322-522 mg/l. The ranges of sodium, calcium, magnesium, chloride, sulphate, nitrate and sodium adsorption ratio were 13-34 mg/l, 32.27-86.34 mg/l, 35.0-67.8 mg/l, 29-88 mg/l, 129-254 mg/l, 0.9-3.6 µg N-NO3/l and 1.62-4.99 meq/l respectively. The values for the water quality index (WQI) were varied from 72.14 to 72.36 that categorized within category three (fair). The lowest value was recorded at station 2 while the highest was encountered from station 1. The results revealed that the quality of Himreen Lake water was suitable for irrigation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".