Evaluation of water quality and eutrophication status of Hawassa Lake based on different water quality indices
Bibliographic record
Abstract
Abstract Lake Hawassa is one of the major Ethiopian Rift Valley Lakes having an endorheic basin system. The surrounding community makes use of the lake water for the multiple purposes of irrigation, domestic water supply, recreation and fish harvesting. The aim of the present study was to ascertain the water quality of the lake in terms of water quality indices (WQI) and its health over a period of three months covering both dry and wet seasons. Overall, the water quality of Lake was unfit and bad as per the weighted arithmetic method (120.06–228.29) and modified Bascarón water quality index (MBWQI) methods (26.81–33.89), respectively. However, the quality was indicated as marginal, as per the Canadian Council of Ministers of the Environment (CCME) water quality index method (44.2–51.1). On average, the lake was under the hypertrophic stage as per the standard based on the results of Secchi depth and nutrient concentration. The current study showed the lake being unfit for all-purposes as per WAWQI range (> 100). According to the physicochemical and biological parameters, of the lake, it requires mitigation measures to control Eutrophication and pollutants inflow.
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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 | 0.000 | 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".