Impact of Water Chemistry on Lead Carbonate Dissolution in Drinking Water Distribution Systems
Bibliographic record
Abstract
Elemental lead is a known toxic metal that can pose threats to human health and can be found in a variety of sources including drinking water at very low level concentrations (i.e. μg/L range). Destabilization of the corrosion scale at the inner layer of pipeline is the major source of lead in drinking water. Chemical properties of the water passing through the distribution system such as pH, alkalinity, chlorine content, oxidation reduction potential (ORP) and natural organic matters will affect the formation and/or destabilization of the corrosion scale. This research examines the impact of pH values (7.0 - 9.5), temperatures (5°C vs 20°C) and alkalinity levels (moderate vs low), in the presence of chlorine, on dissolution of hydrocerussite and cerussite in drinking water by various sets of batch dissolution experiments. The results showed dissolution of cerussite and hydrocerussite was not impacted significantly by pH ranging 7.0 - 9.5. In addition, and somewhat surprisingly, cold temperature (5°C) and moderate alkalinity showed a great influence on decreasing the solubility of lead species.
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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 | 0.001 |
| 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 | 0.000 | 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".