The concept of persistence as applied to metals for aquatic hazard identification
Bibliographic record
Abstract
The criteria persistence (P), bioaccumulation (B), and toxicity (T) are applied by domestic and international regulators and modelers to the hazard identification of chemical substances, including metals and metalloids, that may present harm to the environment. In this paper, we critically examine the literature to determine the weight of evidence for the application of water column partition half-times as a surrogate for the persistence criterion in the aquatic hazard identification of metals and metal compounds. Dissolved metals such as Fe, Mn, Cu, Pb, Co, Cs, Hg, and Zn, as well as the metalloids As and Se, tend to partition from the water column by adsorption onto sinking particulates, with reported and calculated partition half-times in the range 4 to 30 d, with outliers of 0.07 and 280 d. Within freshwater lakes, values of t1/2 for the transition metals Cr, Mn, Fe, Co, and Cu averaged about 10 d, while those for the nontransition metals Sr, Zn, Cs, and Hg and the metalloids As and Se varied up to 55 d. These data are consistent with the well-established complexing properties of the transition metals, which are significantly greater compared to the nontransition metals and the metalloids. While the considerable variations in the literature at present preclude the use of metal partition half-times in aquatic hazard identification, the surrogate for the persistence criterion could be the partition half-time of the bioavailable fraction of the total dissolved metal concentration as determined in a laboratory protocol under standardized conditions.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.003 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".