Analysis of worldwide regulatory guidance for surface soil contamination
Bibliographic record
Abstract
Regulations are emerging worldwide to address surface soil contamination. Many of these use regulatory guidance values (RGVs) to specify concentrations above which action is required. However, because so many independent jurisdictions develop these values, the results are highly variable. Recent studies have demonstrated that the RGVs used by US states vary by several orders of magnitude. This manuscript presents results from an effort that identified 62 surface soil RGV datasets containing 3574 values from 31 other nations and compiled them into a database titled International Surface Soil Regulatory Guidance Values (IS2RGV). Analysis indicates that there are also orders of magnitude variability in the RGVs used worldwide, and that this variability has much in common with US state RGV variability. Results are presented for the 30 most frequently regulated organic, 20 most frequently regulated inorganic, and all regulated element contaminants. Trichloroethylene, cyanide, and mercury are used to illustrate how worldwide RGV variability compares with that of US states, and how data may be commingled to help identify emerging consensuses.
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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 | 0.014 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.023 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".