Status and trends of water quality in the Tafna catchment: a comparative study using water quality indices
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Water quality indices (WQIs) are necessary for resolving lengthy, multi-parameter, water analysis reports into single digit scores; different WQIs have been developed worldwide which are greatly differing in terms of mathematical structures, the numbers and types of variables included, etc. The aim of this paper is to evaluate trends of water quality in Tafna basin with a comparison of 10 WQIs perceived as the most important indices for water quality assessment. The results show that there is an appreciable difference between indices values for the same water sample. The results also show that water quality categorization for sampling stations in the Canadian Council of Ministers of the Environment WQI (CCMEWQI) and British Columbia WQI (BCWQI) was found to be ‘marginal’ for all sampling stations, except Hammam Boughrara reservoir and Mouillah wadi where it was found to be ‘poor’. For the Aquatic Toxicity Index, it was found to be ‘totally unsuitable for normal fish life’ for all stations and ‘suitable only for hardy fish species' for Mouillah wadi and Boughrara reservoir. The results show that this transboundary catchment always needs strategies for more effective pollution control management. Future use of WQIs in this way should prove a valuable tool for environmental planning decision-makers in tracking water quality change.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it