Pilot Plant Study to Utilize Waste Brine Generated by Salt Industries
Bibliographic record
Abstract
Since early 80s, people of Pakistan have been enjoying good quality of salt known as refined salt. Mechanical salt washing is used in many countries to upgrade salt quality. The counter current washing at multiple stages and dewatering by centrifuge improves salt quality. During this process almost 10 to 15% of salt is converted into saturated brine solution containing high amount of sodium chloride, calcium, magnesium, potassium and sulphate. In the current practice most of the salt processers, this brine waste solution is drained. In the present study, a method is modified to utilize this waste brine solution. Brine was treated with calcium oxide and iron chloride to remove some soluble and insoluble impurities. The treated brine is evaporated in a specially constructed jacketed crystallizer connected with a hot water geyser. Heat is transferred through bottom by counter current flow. The temperature is maintained between 55 to 65oC at pH 3-4. The applied study yield the well shaped pyramidal crystals of salt known as Fluer de sel (flower of salt), that are world famous and used in gourmet foods with a growing market. Fleur de Sel has unique morphology, lower bulk density, large surface area, improved taste and rapid dissolution as compared to the common cubic salt
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".