Economically Motivated Adulteration of Lemon Juice: Cavity Ring Down Spectroscopy in Comparison with Isotope Ratio Mass Spectrometry: Round-Robin Study
Bibliographic record
Abstract
Background: Economically motivated adulteration (EMA) of foods has become an increasing concern in recent years, with lemon juice as a popular target. Objective and Method: In this work, an optimized preparation procedure for the isolation of citric acid from lemon juice was validated using elemental analyzer-isotope ratio MS (EA-IRMS) to detect adulteration with exogenous citric acid. Additionally, 69 imported lemon juice samples were evaluated using combustion module-cavity ring down spectrometry (CM-CRDS) and compared with the well-established EA-IRMS. Equivalency of CM-CRDS to EA-IRMS was further demonstrated by conducting a round-robin study involving eight laboratories throughout the United States, Canada, and New Zealand. Results: Overall, the results obtained for CM-CRDS were statistically indistinguishable from the results obtained using EA-IRMS for EMA lemon juice analysis. Conclusions: Therefore, CM-CRDS is a viable option for this application. Highlights: The CM-CRDS instrumentation is easy to operate, robust, and provides δ13C values comparable to EA-IRMS for citrate analysis. Through a multi-laboratory exercise, CM-CRDS was shown to be an alternative to EA-IRMS in the detection of economic adulteration of lemon juice.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".