The reactions of H <sub>3</sub> O <sup>+</sup> , NO <sup>+</sup> and O with several flavourant esters studied using selected ion flow tube mass spectrometry
Bibliographic record
Abstract
The reactions of H(3)O(+), NO(+), and O(2) (+) with nineteen ester compounds occurring naturally in plants, and having important flavourant properties, were examined using selected ion flow tube mass spectrometry (SIFT-MS). The H(3)O(+) reactions primarily generate [R(1)COOR(2).H](+), and may also produce [R(2)](+) fragment ions and/or fragmentation within the ester linkage. Collisional association/adduct ions, [R(1)COOR(2).NO](+), are the main products formed in the NO(+) reactions, although the carboxyl fragment ion is also detected frequently. The identification of the parent compound may be made more easily in the H(3)O(+) and NO(+) reactions. The inclusion of O(2) (+) reactions in the analysis provides additional information, which may be applied when the identity of a parent compound cannot be determined solely from the H(3)O(+) and NO(+) analysis. Consideration of the product ions generated with the three precursors suggests that SIFT-MS can differentiate between many of the esters investigated, including isomers, although the product ions generated in the reactions with some esters are too similar to allow independent quantification. Our data therefore suggest that SIFT-MS may be a useful tool to rapidly analyse and quantify flavourant esters in complex gas 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".