Puffing as a totally green method for monitoring of hot/cold lime softening process
Bibliographic record
Abstract
Hot/cold lime softening process (LSP) is an established process for water conditioning. LSP is currently monitored with various chemical analyses such as measuring simple and total alkalinities, pH, and hardness of softened water. The current monitoring is a labor-intensive task, which consumes various chemicals and generates a considerable amount of chemical wastewater during daily routine tests. Experiences in many industrial softeners show that the results of the traditional chemical method are not often conclusive. In this work, the weakness of the current chemical method for LSP monitoring has been experimentally verified and the effectiveness of an eco-friendly clean technology, based on puffing, has been introduced. The new method functions via comparing the measured electrical conductivities of softened water before and after puffing. As a totally green method, it has several advantages such as lack of need for any chemical reagent, easy and reliable testing, significant reduction in test costs, and chemical wastes compared to the conventional chemical method.
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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) | 0.001 | 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 | 0.001 | 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".