QUANTITATIVE DOUBLE ANTIBODY SANDWICH ELISA FOR THE DETERMINATION OF GLIADIN
Bibliographic record
Abstract
A sensitive double antibody sandwich ELISA (DAS-ELISA) based on chicken anti-gliadin IgY and biotinylated monoclonal antibody (mAb) was developed for the quantification of gliadin in foods. The anti-gliadin IgY and mAb specifically detected gliadin in wheat, barley, and rye by indirect ELISA and Western-blot assay. Using anti-gliadin IgY as capture antibody and biotinylated mAb as detecting antibody, the sensitivity of DAS-ELISA has a linear standard range of 4-40 ng/mL, showing that the limit of detection (LOD) corresponds to 4 ng/mL gliadin in assay buffer, equivalent to 0.8 ppm in foods. The intra-assay expressed as percentage of coefficients of variation (%CV) was 7.25% average of six food samples. The interassay precision was 9.51% in food samples. The combination of anti-gliadin IgY and biotinylated mAb in the DAS-ELISA provides a reliable, sensitive, and inexpensive tool for the detection of gliadin in gluten-free and gluten-containing food products.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".