Impacts of implementing a corrosion control strategy on biofilm growth
Bibliographic record
Abstract
Biofilm growth and corrosion are interrelated processes in a drinking water distribution system. The presence of corrosion tubercles alters the quality of the water in many ways, such as increasing the number of available attachment sites on the walls of the pipes for bacteria. Moreover, the presence of corrosion by-products significantly reduces chlorine disinfection and the efficiency of biofilm control. This study is aimed at evaluating the effect of implementing a corrosion control program on the development of biofilm on distribution system pipe walls. No impacts were found during full-scale experimentation, however the results of a pilot-scale study carried out with annular reactors showed that, both in the presence and absence of corrosion by-products, the anti-corrosion chemicals tested (orthophosphates, a blend of ortho-polyphosphates, and sodium silicates) had no impact on biofilm development at the concentrations tested. Higher numbers of bacteria fixed on the walls of the reactors wereassociated with larger corrosion deposits on the annular reactors. Removing these corrosion deposits may have a positive impact on biofilm control in a distribution system.
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 | 0.001 | 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 | 0.001 | 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".