δ<sup>34</sup>S Measurements of Sulfur by Multicollector Inductively Coupled Plasma Mass Spectrometry
Bibliographic record
Abstract
An accurate and precise method for the determination of delta34S measurements by multicollector inductively coupled plasma mass spectrometry has been developed. Full uncertainty budgets, taking into consideration all the uncertainties of the measurement process, have been calculated. The technique was evaluated by comparing measured values with a range of isotopically enriched sulfur solutions prepared by gravimetric addition of a 34S spike. The gravimetric and measured results exhibited a correlation of R2 >0.999. Repeat measurements were also made after adding Na (up to 420 microg g(-1)) and Ca (up to 400 microg g(-1)) salts to the sulfur standard. No significant deviations in the delta34S values were observed. The Russell correction expression (Ingle, C.; Sharp, B.; Horstwood, M.; Parrish, R.; Lewis, D. J. J. Anal. At. Spectrom. 2003, 18, 219) was used to correct for mass bias on the 34S/32S isotope amount ratio from the mass bias observed for the 30Si/28Si isotope amount ratio. Consistent compensation for instrumental mass bias was achieved. Resolution of the measured delta34S values was better than 1 per thousand after consideration of all uncertainty components. The technique was evaluated for practical applications by measurement of delta34S for a range of mineral waters by pneumatic nebulization sample introduction and the analysis of genuine and counterfeit pharmaceuticals using both laser ablation sample introduction and liquid chromatography. For the former two cases polyatomic interferences were resolved by operating the MC-ICPMS in medium resolution, while for the chromatographic analyses polyatomic interferences were minimized by the use of a membrane desolvator, allowing the instrument to be operated at a resolution of 400.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".