Characterization and Field Application Assessment Of Prosopis Cineraria (L.) For Fluoride Sequestration: A Preliminary Investigation
Bibliographic record
Abstract
Endemic fluorosis is a worldwide issue affecting potable water security, necessitating the development of economic and elementary fluoride remediation techniques.Recent studies have focused significantly on chemically and thermally modified bio-sorbents to increase fluoride removal efficiency.The current study investigates the potential of a calcium-rich (Ca), untapped biomass Prosopis cineraria (L.) Druce under minimal treatment.Although limited work has explored the remediation of contaminants using the proposed adsorbent in different forms, the usage of Prosopis cineraria carbon (PCC) for fluoride elimination from an aqueous solution is unexplored.Characterization and water quality index of PCC were studied to corroborate results for physical fluoride remediation.Confirming its efficacy as a fluoride scavenger, the synthesized PCC could remove between 79.7 and 87% of the fluoride from initial concentrations in groundwater.
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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 | 0.000 |
| 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) | 0.001 | 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".