A Review on Factors to be Incorporated in Water Quality Study
Bibliographic record
Abstract
Water quality issues had been the main concern in worldwide as water resource keeps being polluted. River acts as the main source of drinking water, habitat for aquatic life, agriculture and industry. Poor in water quality led to the increase n water treatment expenses, water scarcity and affect health. River pollution is caused by industrial discharge, sewage and wastewater, chemical fertilizers and pesticides and mining activities. This paper aims to review and comments on factors to be incorporated in water quality study. Water quality index and pollutants are found to be the critical factors. USA, Canada, Iraq, Thailand, Vietnam and Malaysia used different parameters in calculating WQI. The parameters being considered in the WQI are then classified the river according to their classes and usage. Department of Environment (DOE) Malaysia has highlighted three main pollutants in water quality study which are Biochemical Oxygen Demand (BOD), Ammoniacal Nitrogen (NH3N) and Suspended Solid (SS) due to their great influence on WQI calculation. However, standard treated water quality in Malaysia is still based on Environmental Quality Act, 1974 which is nearly 50 years ago. Emerging pollutants which are mainly organic compounds present as pharmaceuticals and personal care products are found in water resources nowadays and the treatment should be improvised along time. Some modification of class on usage of water as irrigation should be considered and the relevant of considering two oxygen demands in calculating WQI (BOD and COD).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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; both teacher heads agree on what is shown here.
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".