Understanding the Impact of Extracellular Polymeric Substances on Lead Release in Drinking Water Systems
Bibliographic record
Abstract
Abstract Lead release in a lead (Pb, anode)–iron oxide (α-Fe2O3, cathode) galvanic system was studied under the influence of synthetic extracellular polymeric substances (sEPS). Sodium alginate, bovine serum albumin (BSA), and cytochrome c represented extracellular polysaccharides, proteins, and electrochemically active components, respectively. Microbiologically influenced corrosion was investigated using sEPS and pelleted and resuspended Pseudomonas aeruginosa cells. Relative to the anaerobic inorganic control, Pb release increased by 156, 202, and 198 μg/L when sEPS was present on the cathode side at 200 mg/L (100 mg/L alginate + 100 mg/L BSA), 400 mg/L (200 mg/L alginate + 200 mg/L BSA), and 200 mg/L with 123.84 mg/L cytochrome c, respectively, under anaerobic conditions. When the cathode was aerated, Pb release increased by 75, 260, and −71 μg/L under the aforementioned conditions, all relative to the aerated inorganic control. When sEPS was instead present on the anode side, sEPS caused localized corrosion on Pb and resulted in higher Pb release than predicted by electric current. P. aeruginosa generally enhanced corrosion; when cells were dosed in the anode side, part of the oxidized Pb was immobilized by cells or organic compounds adhered to the electrodes.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 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".