Determination of Te, As, Bi, Sb and Se (TABS) in Geological Reference Materials and Geo<i>PT</i> Proficiency Test Materials by Hydride Generation‐Atomic Fluorescence Spectrometry (HG‐AFS)
Bibliographic record
Abstract
The study of Te, As, Bi, Sb and Se (TABS) has increased over the past years due to their use in the development of low‐carbon energy technologies. However, there is a scarcity of mass fraction values of TABS in geological reference materials. This underlines the difficulty in undertaking routine determinations of these elements. The mass fractions of TABS were determined in geological reference materials using hydride generation‐atomic fluorescence spectrometry (HG‐AFS), calibrated with standard solutions. Comparisons with literature values were used to validate the method. Samples from the Geo PT proficiency test were also analysed. For most elements, there are no assigned or even provisional values for many of the Geo PT and reference materials because of the wide range of results reported. For mass fractions above the quantification limit of the method, our results are in good agreement with the median of Geo PT results. Thus, we propose Geo PT median values as informational values for these elements. In contrast, at mass fractions < 0.5 µg g −1 median values of Se from Geo PT are systematically higher than our results. Our Se results are in agreement with the reference materials down to 0.02 µg g −1 , which suggest that many of the results for Se reported in Geo PT testing are too high.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".