Variation in North American regulatory guidance for heavy metal surface soil contamination at commercial and industrial sites
Bibliographic record
Abstract
The health implications and remediation obligations of contaminated soils are significant issues in many urban areas of North America. For commercial and industrial sites, health concerns impact brownfield redevelopment and the conversion of fallow private land into public resources. To help manage health risks, regulatory agencies provide guidance values to identify maximum acceptable levels of contamination. Currently, these guidance values differ by as much as 5 orders of magnitude for some metals. The variability in North American guidance for Cd, Cr, Cu, Ni, Pb, and Zn surface soil contamination at commercial and industrial sites is examined. Ordered column diagrams illustrate the magnitude and dispersion of guidance values. Statistical analysis is used to investigate the significance of variations. Results indicate that commercial and industrial site guidance is more variable than residential site guidance and that even when the values are treated as lognormal random variables, some appear to be “uncharacteristic” outliers. The most significant regional trends are differences between US and Canadian guidance, but individual jurisdiction differences dominate over regional trends. When current guidance values sets were used in Hazard Index analysis applied to 20 sample urban brownfield sites, the results varied by 2 orders of magnitude.
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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".