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 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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".