Improved Detection of Sugar Addition to Maple Syrup Using Malic Acid as Internal Standard and in <sup>13</sup>C Isotope Ratio Mass Spectrometry (IRMS)
Bibliographic record
Abstract
Stable carbon isotope ratio mass spectrometry (delta13C IRMS) was used to detect maple syrup adulteration by exogenous sugar addition (beet and cane sugar). Malic acid present in maple syrup is proposed as an isotopic internal standard to improve actual adulteration detection levels. A lead precipitation method has been modified to isolate quantitatively malic acid from maple syrup using preparative reversed-phase liquid chromatography. The stable carbon isotopic ratio of malic acid isolated from this procedure shows an excellent accuracy and repeatability of 0.01 and 0.1 per thousand respectively, confirming that the modified lead precipitation method is an isotopic fractionation-free process. A new approach is proposed to detect adulteration based on the correlation existing between the delta13Cmalic acid and the delta13Csugars-delta13Cmalic acid (r = 0.704). This technique has been tested on a set of 56 authentic maple syrup samples. Additionally, authentic samples were spiked with exogeneous sugars. The mean theoretical detection level was statistically lowered using this technique in comparison with the usual two-standard deviation approach, especially when maple syrup is adulterated with beet sugar : 24 +/- 12% of adulteration detection versus 48 +/- 20% (t-test, p = 7.3 x 10-15). The method was also applied to published data for pineapple juices and honey with the same improvement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".