One in Four US Households Likely Exceed New Soil Lead Guidance Levels
Bibliographic record
Abstract
Lead exposure has blighted communities across the United States (and the globe), with much of the burden resting on lower income communities, and communities of color. On 17 January 2024, the US Environmental Protection Agency (USEPA) lowered the recommended screening level of lead in residential soils from 400 to 200 parts per million. Our analysis of tens of thousands of citizen-science collected soil samples from cities and communities around the US indicates that nearly one quarter of households may contain soil lead that exceed the new screening level. Extrapolating across the nation, that equates to nearly 30 million households needing to mitigate potential soil lead hazards, at a potential total cost of 290 billion to $1.2 trillion. We do not think this type of mitigation is feasible at the massive scale required and we have instead focused on a more immediate, far cheaper strategy: capping current soils with clean soils and/or mulch. At a fraction of the cost and labor of disruptive conventional soil mitigation, it yields immediate and potentially life-changing benefits for those living in these environments.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".