Next steps in the development of ecological soil clean-up values for metals
Bibliographic record
Abstract
Abstract This special series in Integrated Environmental Assessment Management presents the results from 6 workgroups that were formed at the workshop on Ecological Soil Levels—Next Steps in the Development of Metal Clean-Up Values (17–21 September 2012, Sundance, Utah). This introductory article presents an overview of the issues assessors face when conducting risk assessments for metals in soils, key US Environmental Protection Agency (USEPA) documents on metals risk assessment, and discusses the importance of leveraging from recent major terrestrial research projects, primarily to address Registration, Evaluation, Authorization and Restriction of Chemical Substances (REACH) requirements in Europe, that have significantly advanced our understanding of the behavior and toxicity of metals in soils. These projects developed large data sets that are useful for the risk assessment of metals in soil environments. The workshop attendees met to work toward developing a process for establishing ecological soil clean-up values (Eco-SCVs). The goal of the workshop was to progress from ecological soil screening values (Eco-SSLs) to final clean-up values by providing regulators with the methods and processes to incorporate bioavailability, normalize toxicity thresholds, address food-web issues, and incorporate background concentrations. The REACH data sets were used by workshop participants as case studies in the development of the ecological standards for soils. The workshop attendees discussed scientific advancements in bioavailability, soil biota and wildlife case studies, soil processes, and food-chain modeling. In addition, one of the workgroups discussed the processes needed to frame the topics to gain regulatory acceptance as a directive or guidance by Canada, the USEPA, or the United States. Integr Environ Assess Manag 2014;10:342–345. © 2013 The Authors. Integrated Environmental Assessment and Management Published by SETAC Key Points World expert workshop attendees on metals risk assessment issues met to work toward developing a process for establishing ecological soil clean-up values (Eco-SCVs) for metals. The goal of the workshop was to progress from ecological soil screening values (Eco-SSLs) to final clean-up values by providing regulators with methods and processes to incorporate bioavailability, normalize toxicity thresholds, address food-web issues, and incorporate background concentrations. The REACH data sets were used by workshop participants as case studies in the development of ecological standards for metals in soils. The special series publications are compilations of state-of-the-art information and provide usable recommendations on metal bioavailability, soil processes, food-chain modeling, and the procedures needed to frame the topics to gain regulatory acceptance of soil biota and wildlife clean-up values.
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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 | 0.045 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".