Water Quality of Underground Wells in Limoeiro do Norte, Brazilian Northeast
Bibliographic record
Abstract
The objective of this work was to assess the physicochemical and microbiological characteristics, as well as the potential of salinization and sodification of groundwater wells in Limoeiro do Norte, Ceará states, Brazil. Six water wells were selected for the study, all of them used for irrigation and human consumption. The ionic classification was performed by Piper Diagram and the salinity risk using the U.S.S.L. (United States Salinity Laboratory) Diagram using Qualigraf software. Based on the average chemical element concentration (mmolc L-1) in the groundwater, the following quantification is obtained: Na+ > Ca2+ > Mg2+ > K+ for cations. For anions there was a change in the the wells, for the 1, 3 and 4 Cl- > HCO3- > SO42- > CO32- and wells 2, 5 and 6 HCO3- > Cl- > SO42- > CO32-. The wells 1, 2 and 3 have severe restrictions for use by SAR (sodium absorption ratio) and Na+ content. Water from wells 1, 3 and 5 were classified as sodium chloride, 2 and 6 were classified as sodium bicarbonate and well 4 as calcium magnesium sulfate. With the exception of well 6 classified as freshwater, all other wells were classified as brackish water. Groundwater samples fall in C3S1 or C3S2 category with high salinity and low or medium sodium hazard. With the exception of Na+, whose value was above the limit allowed, no well with groundwater was detected chemical hazard for human consumption. There was the detection of Total coliforms, but in well 5 the presence of Thermotolerant coliforms was detected.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".