Sulfur Kβ X-ray emission spectroscopy: comparison with sulfur K-edge X-ray absorption spectroscopy for speciation of organosulfur compounds
Bibliographic record
Abstract
Until recently, sulfur was known as a "spectroscopically silent" element because of a paucity of convenient spectroscopic probes suitable for in situ chemical speciation. In recent years the technique of sulfur K-edge X-ray absorption spectroscopy (XAS) has been used extensively in sulfur speciation in a variety of different fields. With an initial focus on reduced forms of organic sulfur, we have explored a complementary X-ray based spectroscopy - sulfur Kβ X-ray emission spectroscopy (XES) - as a potential analytical tool for sulfur speciation in complex samples. We compare and contrast the sensitivity of sulfur Kβ XES with that of sulfur K-edge XAS, and find differing sensitivities for the two techniques. In some cases an approach involving both sulfur K-edge XAS and sulfur Kβ XES may be a powerful combination for deducing sulfur speciation in samples containing complex mixtures.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".