Bibliographic record
Abstract
Determinations of particulate Al (pAl), leachable particulate Al (lpAl), and soluble Al (sAl) along the treatment sequence were used to investigate the occurrence of turbidity at drinking-water plants using aluminum coagulation. The behavior of Al species during filtration was normal when sAl remained at a constant level, while pAl was completely eliminated. When sAl was constant while pAl was not completely eliminated, the presence of residual pAl could be attri buted to problems of filtration effectiveness. When sAl decreased during filtration, the residual pAl could also originate from transformations such as precipitation occurring in the filtration media. When sAl increased, the residual pAl could also originate from precipitate detachments. Increases in sAl during filtration or the presence of partially leachable pAl were associated with deteriorations in residual pAl along filtration runs. The presence of nonleachable pAl denoted the existence of different aluminum forms. This was a supplementary indicator of treatment problems and affected the relationship with turbidity. In addition to demonstrating the occurrence of aluminum turbidity, speciation analysis offered a characterization of turbidity and its origin. By contributing to the evidence as well as the understanding of treatment problems, these speciation methodologies can be useful to minimize aluminum turbidity.
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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 | 0.001 |
| 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) | 0.000 | 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".