Fluorescence Analysis of Quinine in Commercial Tonic Waters
Bibliographic record
Abstract
Quinine is known for treating malaria, muscle cramps, and, more recently, has been used as an additive in tonic water due to its bitter taste. However, it was shown that excessive consumption of quinine can have severe side effects on health. In this work, we utilized fluorescence spectroscopy to measure the concentration of quinine in commercial tonic water samples. An external standard method was used to calculate the concentrations of quinine in two commercially available tonic water brands, namely Canada Dry and Schweppes, and compare them to the maximum allowable concentration of quinine in beverages. Upon analysis of the data collected by five different groups, the levels of quinine were found to be above the average concentration in most commercial tonic water samples, but below the maximum permitted concentration. Moreover, the five replicate sets of data demonstrated high reproducibility of the method employed in this study. The simple yet instructive protocol that we developed can be adapted to determine the concentration of other fluorescent compounds in foods and beverages. Further, the presented method and detailed protocol can be easily adopted for undergraduate labs and in chemical education.
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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 | 0.001 |
| 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".