Synthesis of isotope-labelled methoxypyrazine compounds as internal standards and quantitative determination of aroma methoxypyrazines in water and wines by solid-phase extraction with isotope dilution-GC-MS /
Bibliographic record
Abstract
An efficient way of synthesizing the deuterium labelled analogues of three \nmethoxypyrazine compounds: 2-d3-methoxy-3-isopropylpyrazine, 2-d3-methoxy-3- \nisobutylpyrazine, and 2-d3-methoxy-3-secbutylpyrazine, has been developed. To confirm \nthat the deuterium labels had been incorporated into the expected positions in the \nmolecules synthesized, the relevant characterization by NMR, HRMS and GC/MS \nanalysis was conducted. Another part of this work involved quantitative determination of \nmethoxypyrazines in water and wines. Solid-phase extraction (SPE) proved to be a \nsuitable means for the sample separation and concentration prior to GC/MS analysis.Such factors as the presence of ethanol, salt, and acid have been investigated which can \ninfluence the recovery by SPE for the pyrazines from the water matrix. Significantly, in \nthis work comparatively simple fractional distillation was attempted to replace the \nconventional steam distillation for pre-concentrating a sample with a relatively large \nvolume prior to SPE. Finally, a real wine sample spiked with the relevant isotope-labelled \nmethoxypyrazines was quantitatively analyzed, revealing that the wine with 10 beetles \nper litre contained 138 ppt of 2-methoxy-3-isopropylpyrazine. Interestingly, we have also \nfound that 2-methoxy-3-secbutylpyrazine exhibits an extremely low detection limit in \nGC/MS analysis compared with the detection limit of the other two methoxypyrazines: 2- \nmethoxy-3-isopropylpyrazine and 2-methoxy-3-isobutylpyrazine.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".