Determination of Concentration of Food Dyes in Powdered Drink Mixes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Federal Food, Drug, and Cosmetic Act (FD&C) food dyes make industrial goods like foods and beverages more appealing. These dyes are synthetic and are typically used instead of natural dyes due to their color, stability, and low cost. Research has implied that children are sensitive to the amount of food dye in products. The amount of food dye in products is proprietary information, so it can be challenging to determine how much dye children are ingesting. In this study, ultraviolet-visible spectroscopy (UV-Vis) was utilized to find the concentration of food dyes in various powdered drink mixes. The results show that powdered drink mixes containing Red 40 have higher concentrations of food dye than the rest of the drink mixes. Our data supports that there is a difference between the concentrations of food dyes within drink mixes containing Red 40 versus those without it. These concentrations depend on the dye and how many dyes were in the drink mix.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 it