Weight-of-Evidence Approach for Assessing Removal of Metals from the Water Column for Chronic Environmental Hazard Classification
Bibliographic record
Abstract
The United Nations and the European Union have developed guidelines for the assessment of long-term (chronic) chemical environmental hazards. This approach recognizes that these hazards are often related to spillage of chemicals into freshwater environments. The goal of the present study was to examine the concept of metal ion removal from the water column in the context of hazard assessment and classification. We propose a weight-of-evidence approach that assesses several aspects of metals including the intrinsic properties of metals, the rate at which metals bind to particles in the water column and settle, the transformation of metals to nonavailable and nontoxic forms, and the potential for remobilization of metals from sediment. We developed a test method to quantify metal removal in aqueous systems: the extended transformation/dissolution protocol (T/DP-E). The method is based on that of the Organisation for Economic Co-operation and Development (OECD). The key element of the protocol extension is the addition of substrate particles (as found in nature), allowing the removal processes to occur. The present study focused on extending this test to support the assessment of metal removal from aqueous systems, equivalent to the concept of "degradability" for organic chemicals. Although the technical aspects of our proposed method are different from the OECD method for organics, its use for hazard classification is equivalent. Models were developed providing mechanistic insight into processes occurring during the T/DP-E method. Some metals, such as copper, rapidly decreased (within 96 h) under the 70% threshold criterion, whereas others, such as strontium, did not. A variety of method variables were evaluated and optimized to allow for a reproducible, realistic hazard classification method that mimics reasonable worst-case scenarios. We propose that this method be standardized for OECD hazard classification via round robin (ring) testing to ascertain its intra- and interlaboratory variability. Environ Toxicol Chem 2019;38:1839-1849. © 2019 SETAC.
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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 | 0.130 | 0.242 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.012 |
| Bibliometrics | 0.033 | 0.009 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".