Quantification of Methanol in the Presence of Ethanol by Selected Ion Flow Tube Mass Spectrometry
Bibliographic record
Abstract
The quantification of trace compounds in alcoholic beverages is a useful means to both investigate the chemical basis of beverage flavor and to facilitate quality control during the production process. One compound of interest is methanol which, due to it being toxic, must not exceed regulatory limits. The analysis of headspace gases is a desirable means to do this since it does not require direct sampling of the liquid material. One established means to conduct headspace analysis is selected ion flow tube mass spectrometry (SIFT-MS). The high concentration of ethanol present in the headspace of alcoholic drinks complicates the analysis, however, via reacting with the precursor ions central to this technique. We therefore investigated whether methanol could be quantified in the presence of a large excess of ethanol using SIFT-MS. We found that methanol reacted with ionized ethanol to generate product ions that could be used to quantify methanol concentrations and used this technique to quantify methanol in beverages containing different quantities of ethanol. We conclude that SIFT-MS can be used to quantify trace compounds in alcoholic beverages by determining the relevant reaction chemistry.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.000 | 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".