Comparison of nickel speciation in workplace aerosol samples using sequential extraction analysis and X-ray absorption near-edge structure spectroscopy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
There is a pressing need to further develop speciation knowledge of Ni workplace aerosols as the Zatka sequential extraction method used until now to speciate workplace Ni exposures has limitations. Here we compare the Zatka and XANES methods and evaluate XANES spectroscopy as a more appropriate and accurate technique for identifying nickel species in workplace aerosols. XANES spectroscopy is capable of identifying unique Ni species in the unaltered samples. Our findings indicate some significant departures in speciation assignment between the Zatka and XANES methods. In particular, the Zatka method can overestimate the soluble Ni fraction and it may underestimate the sulphidic and metallic fractions in some samples. Of particular importance, XANES is able to identify component sulphidic species. This information can lead to more accurate exposure matrices and more refined epidemiological analysis of respiratory cancer causation in sulphidic Ni processing.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it