Transformation/dissolution characteristics of a nickel matte and nickel concentrates for acute and chronic hazard classification
Bibliographic record
Abstract
Abstract For the purposes of aquatic hazard classification under the United Nations Globally Harmonized System of Classification (UNGHS), we have examined the transformation/dissolution (T/D) characteristics of a Ni matte and 4 Ni concentrates at pH 6 using the United Nations (UN) Transformation/Dissolution Protocol (T/DP) for metals and sparingly soluble metal compounds. Among the analytes Ni, Co, and Cu, Ni was released into the T/D solutions in the highest concentrations and was thus the main driver in establishing the hazard classification. We applied an extrapolation-scaling approach to obtain concentrations of total dissolved Ni at low loadings of 0.1 and 0.01 mg/L for derivation of chronic classification outcomes in the European Union (EU) classification, labeling, and packaging (CLP) scheme. The T/D data would classify the Ni matte as Acute 2-Chronic 2 under the Globally Harmonized System (GHS) scheme, and Chronic 1 under the EU CLP. Three of the 4 Ni concentrates would classify as GHS Acute 2-Chronic 2 and EU CLP Chronic 2, whereas the 4th would classify as GHS Acute 3-Chronic 3 and EU CLP Chronic 3. In applying the critical surface area (CSA) approach to the Ni concentrates, acute and chronic hazard classification outcomes were the same as those derived from direct application of the T/D data to the GHS and EU schemes. Such agreement provided confidence that the CSA approach could yield scientifically defensible acute and chronic hazard classification outcomes. Integr Environ Assess Manag 2015;11:130–142. © 2014 SETAC Key Points Using T/D (Transformation/Dissolution) research, we have shown how an extrapolation-scaling approach can be used to derive chronic hazard classification outcomes under the UN Globally Harmonized System of Classification and Labelling (GHS) and the EU Classification, Packaging and Labelling Regulation (CLP) for a Ni matte and Ni concentrates. These outcomes are mandatory for producers users and importers of chemical substances to protect the environment and to secure and expand on their markets within the European Union and other jurisdictions. The approach was needed because of the requirement to estimate metal concentrations at T/D loadings of 0.1 and 0.01 mg/L, which are unattainable under normal laboratory conditions. Based on extrapolation-scaling, the Ni matte would classify as EU CLP Chronic 1, while the chronic classification outcomes for three of the Ni concentrates would be CLP chronic 2 and one would be Chronic 3. These classification outcomes inform producers and users of the measures they neeed to take to protect the environment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".