Site-specific hydrogen isotope measurements of vanillin by 2H-qNMR and GC-IRMS
Bibliographic record
Abstract
Abstract Stable isotope analyses are powerful techniques to detect counterfeiting of food products, especially in vanillin, one of the world’s most popular flavors used in food and pharmaceutical industries. Although a stable carbon isotopic ratio provides an invaluable new source of isotopic information, the analysis of the hydrogen site-specific ( 2 H/ 1 H) isotopic distribution in vanillin gives valuable complementary isotopic information allowing a complete isotopic fingerprint of the vanillin molecule for authentication. However, there are only a limited number of studies that compare the validity of the results obtained by IRMS and NMR. Here, we present site-specific isotope analysis (also known as position-specific isotope analysis, PSIA) of hydrogen isotopic measurements of vanillin by two independent measurement methods, 2 H-qNMR and GC-IRMS, and compare the results obtained by these two methods. 2 H-qNMR allows isotopic measurements of all hydrogen atoms (except for OH) of the vanillin molecule while GC-IRMS measures only the hydrogen atoms of the methoxy group (H5). 2 H/ 1 H values of the vanillin H5 from six vanillin demonstrate remarkable agreement between the two techniques with uncertainty well below 1%. Position-specific GC-IRMS on the methoxy group measurements provides three-fold smaller measurement uncertainties while requiring a considerably smaller sample size compared to 2 H-qNMR. This quantitative hydrogen isotopic study extends our previous successful work comparing and validating the stable carbon isotopic of the vanillin methoxy group using 13 C-qNMR and GC-IRMS. Compound-specific isotope analysis (CSIA) using GC-IRMS was also described in this work. Both qNMR and partial PSIA GC-IRMS can be considered as complementary analytical methods, and their combined use provides reliable results. Graphical Abstract
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".