Hydrochemical Characterization of Water Resources From Reverse Osmosis Desalination Plants
Bibliographic record
Abstract
The desalination of the brackish waters is a technology of coexistence with the semi-arid and its adoption implies in determining the environmental impacts due to the reject brine generated. Therefore, this work evaluated the hydrochemical characteristics of well water (feed water), drinking water (purified) and reject brine from reverse osmosis desalination plants in Western Meso-region, Rio Grande do Norte state, Brazil. During the periods between October 2013 and November 2014, four water samples were taken at seven inland desalination plants in communities and rural settlements. The hydrochemical characteristics of the waters were evaluated using multivariate statistical analysis. The following physico-chemical parameters of water collected were evaluated: electrical conductivity (ECw), pH, concentrations of cations (sodium, potassium, calcium and magnesium) and anions (chloride, carbonate and bicarbonate), Sodium Adsorption Ratio, Langelier Saturation Index, Stability Index of Ryznar, and the Calcium/Magnesium ratio. Well water and reject brine were classified into six groups, while purified water was classified into seven groups with different levels of risk of salinization, sodification and ions toxicity.
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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 | 0.000 | 0.000 |
| 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 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".