Paper-Based Microfluidic Device (DON-Chip) for Rapid and Low-Cost Deoxynivalenol Quantification in Food, Feed, and Feed Ingredients
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
Mycotoxin contamination causes over $5 billion of economic loss per year in the North American food and feed industry. A rapid, low-cost, portable, and reliable method for on-site detection of deoxynivalenol (DON), a representative mycotoxin predominantly occurring in grains, would be helpful to control mycotoxin contamination. In this study, a paper-based microfluidic chip capable of measuring DON (DON-Chip) in food, feed, and feed ingredients was developed. The DON-Chip incorporated a colorimetric competitive immunoassay into a paper microfluidic device and used gold nanoparticles as a signal indicator. Furthermore, a novel ratiometric analysis method was proposed to improve detection resolvability. Detection of DON in the aqueous extracts from solid food, feed, or feed ingredients was successfully validated with a detection range of 0.01–20 ppm (using dilution factors from 10 to 104). Compared with conventional methods, the DON-Chip method could greatly reduce the cost and time of mycotoxin detection in the food and feed industry.
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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