Lead Levels at the Tap and Consumer Exposure from Legacy and Recent Lead Service Line Replacements in Six Utilities
Bibliographic record
Abstract
Profile, regulatory, and investigative sampling were completed in six utilities to study the impact of partial and full lead service line replacements (LSLRs) on water lead levels (WLLs) and consumer's exposure. As compared to households with no replacement, lead release after partial LSLR (PLSLR) was generally greater in the short term (3-50 days), and comparable or lower in the medium (<2 years) and long-term (>2 years). This was mainly explained by insufficient time elapsed to stabilize scales after disturbances to the service line. One utility showed sustained lead release over 18 months after PLSLR. Moreover, the reduction in WLLs was small when analyzing results for the same households. As a comparison, full LSLR decreased WLLs drastically and immediately. The occurrence of low (0-5 μg/L) to high (≥50 μg/L) WLLs in the profiles varied between households and reflected the variability of exposure among households in the same system. Using this probability of occurrence, the distribution of WLLs of exposure was estimated for households with or without a PLSLR, and used to model young children blood lead levels (BLLs) for both groups of households. The range of modeled BLLs decreased slightly for households with PLSLR, but still overlapped the range estimated for households with no replacement. This analysis suggests that, in a system, PLSLRs do not reduce young children blood lead levels except in a fraction of households.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".