Applicability of ELISA methods for high gluten-containing samples
Bibliographic record
Abstract
Quantitation of gluten in gluten-free products is a great challenge as it is hindered by several factors including the lack of certified reference materials. To resolve this problem, our research group, in cooperation with other international experts, started a series of experiments with the goal of the production of a suitable gluten reference material. As a part of this research, several different wheat cultivars and their isolated gluten proteins were characterized by different methods, including enzyme-linked immunosorbent assay (ELISA). However, we need to know the performance of the ELISA methods used for this special area of research. During the present work we investigated the accuracy and precision of two different ELISA methods for our own laboratory conditions and special sample matrices (wheat flours and gliadin isolate). We have found that the tested performance characteristics of the methods seem to be appropriate on a case-by-case basis, but the long-term measurement uncertainty is higher, which makes it difficult to evaluate the results obtained with the ELISA method for these types of samples.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 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".