Measurement of Tartrazine Levels in Children’s Snacks in Banda Aceh Using an Arduino Uno-Based TCS3200 Color Sensor
Bibliographic record
Abstract
This study aims to develop and validate a low-cost method based on TCS3200 color sensor and an Arduino Uno microcontroller with integrated development environment (IDE) software for the determination of tartrazine levels in children's snacks.The measurement results will be compared with the standard UV-Vis spectrophotometer method.Samples were prepared by heating and extracted using wool yarn, from which the attached samples were collected.The sampling technique was conducted on 6 types of snacks sold in Banda Aceh City.The analysis results showed that tartrazine levels ranged from 1.34 to 4.65 ppm using the TCS3200 color sensor, which were consistent with those obtained using UV-Vis spectrophotometer (1.32-4.64ppm).Linearity (R 2 ) and accuracy obtained in this study were 0.987 and 93.2 to 109% for the TCS3200 color sensor, and 0.988 and 93 to 115% for UV-Vis, respectively.The intraday and interday relative standard deviations (%RSD) did not exceed 2%.Based on the t-test calculation, it was shown that the measured tartrazine levels using the TCS3200 color sensor were not significantly different from those obtained using the UV-Vis spectrophotometer.
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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 | 0.001 | 0.001 |
| 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".