Direct Comparison of Cavity Ring Down Spectrometry and Isotope Ratio Mass Spectrometry for Detection of Sugar Adulteration in Honey Samples
Bibliographic record
Abstract
In the last several years, economically motivated adulteration (EMA) of foods including honey has received increased attention. The addition of inexpensive sweeteners such as high fructose corn syrup or cane sugar to honey is still encountered despite scientific methods that can routinely detect this type of adulteration. The standard method for detection of these adulterants utilizes isotope ratio mass spectrometry (IRMS); however, this technique requires an elevated degree of technical knowledge for operation as well as a high cost for purchase and maintenance. Cavity ring down spectroscopy (CRDS) has demonstrated potential for this type of analysis and is less expensive with simpler operation. This study evaluates CRDS for the detection of low-cost sweeteners added to honey and compares the performance of CRDS to IRMS. Several honey samples were analyzed, and the advantages and limitations specific to CRDS were evaluated. Overall, the results indicate that CRDS provides a performance comparable to the benchmark technique IRMS for EMA honey analysis.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".