Factors Affecting Drinking Water Biofiltration
Bibliographic record
Abstract
This research examined several important factors affecting the removal of biodegradable organic matter in drinking water biofilters. Laboratory‐scale biofilters were used and were fed a cocktail of easily biodegradable compounds. The factors investigated were chlorine or chloramine in the backwash water, air scour during backwashing, anthracite/sand versus granular activated carbon (GAC)/sand media, and low (5°C) versus high (20°C) temperature operation. Factorial design experiments showed that the three main factors (chlorine in the backwash water, temperature, and media type) and their interactions were significant in most cases. The temperature effect was more significant when chlorine was present. The GAC filters were much more resistant to chlorinated backwash water than were anthracite filters. Air‐scour effects were generally negligible except in some cases at low temperature with chloramine in the backwash water. Glyoxal removal was more sensitive to unfavorable biofiltration conditions than were removals of acetate, formate, and formaldehyde.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 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".