Hydrogeochemistry of Ground Water in Mbeere South Sub-County, Kenya
Bibliographic record
Abstract
This paper presents the experimental and simulated results of ground water in Mbeere South Sub -County, Kenya. A total of 30 samples from 10 boreholes were collected and used to investigate the chemical characteristics of groundwater. The samples were analyzed for physicochemical characteristics such as pH, temperature and Total Dissolved Solids along with major cations and anions using standard analytical procedures. The laboratory data obtained was run into a hydrogeochemical computer model, PHREEQC for aqueous speciation modelling. Origin pro and AqQA computer software were also used to reveal more hydrogeochemistry of the groundwater in the area. The results showed that the Na+ ˃ Ca2+ ˃ Mg2+ ˃ K+> Fe3+were the dominant cations while HCO3-˃Cl->SO42->NO3-˃F- were the dominant anions. The hydrogeochemical facies indicated that 40% of the samples belong to the Ca2+-Mg2+-Cl--SO42- type, 40% belong to the Ca2+-Mg2+-HCO3-, 20 % are of the type Na+-K+-HCO3- with no Na+-K+-Cl--SO42- water type. The facies also illustrated atmospheric precipitation, dissolution of salt deposits within the vadose zones and weathering of halite, anhydrite, gypsum, huntite, hydromagnesite, artinite, dolomite and magnesite as the major contributors to the variation in Mbeere South groundwater chemistry. The Saturation Indices (SI) showed that the specimens were slightly saturated with aragonite, calcite, and dolomite; slightly under-saturated with anhydrite and gypsum; moderately under saturated with halite and under-saturated with hydromagnesite, trona and portlandite.
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.
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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".