The ecotoxicity of zinc and zinc-containing substances in soil with consideration of metal-moiety approaches and organometal complexes
Bibliographic record
Abstract
Abstract Within Canada, screening-level assessments for chemical substances are required to determine whether the substances pose a risk to human health and/or the environment, and as appropriate, risk management strategies. In response to the volume of metal and metal-containing substances, process efficiencies were introduced using a metal-moiety approach, whereby substances that contain a common metal moiety are assessed simultaneously as a group, with the moiety of concern consisting of the metal ion. However, for certain subgroups, such as organometals or organic metal salts, the organic moiety or parent substance may be of concern, rather than simply the metal ion. To further investigate the need for such additional consideration, certain substances were evaluated: zinc (Zn)-containing inorganic (Zn chloride [ZnCl2] and Zn oxide) and organic (organometal: Zn diethyldithiocarbamate [Zn(DDC)2] and organic metal salts (Zn stearate [ZnSt] and 4-chloro-2-nitrobenzenediazonium tetrachlorozincate [BCNZ]). The toxicity of the substances were assessed using plant (Trifolium pratense and Elymus lanceolatus) and soil invertebrate (Folsomia candida and Eisenia andrei) tests in a sandy soil. Effect measures were determined based on total metal and total parent analyses (for organic substances). In general, the inorganic Zn substances were less toxic than the organometals and organic metal salts, with 50% effective concentrations ranging from 11 to >5194 mg Zn kg−1 dry soil. The data demonstrate the necessity for alternate approaches in the assessment of organo–metal complexes, with the organic moieties or parent substances warranting consideration rather than the metal ion alone. In this instance, the organometals and organic metal salts were significantly more toxic than other test substances despite their low total Zn content. Environ Toxicol Chem 2017;36:3324–3332. © 2017 Crown in the Right of Canada. Published by Wiley Periodicals Inc. on behalf of 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".