Determination of Ochratoxin A in Licorice and Licorice Extracts by High-Performance Liquid Chromatography Coupled with Fluorescence Detection: Collaborative Study
Bibliographic record
Abstract
A collaborative study was conducted to validate an analytical method for the determination of ochratoxin A (OTA) in licorice (root powder) and licorice extracts (paste and powder). Contents of OTA ranged from 26 to 141 microg/kg and from 8 to 52 microg/kg for licorice extracts and root material, respectively. For the analysis, a test portion is extracted with a mixture of methanol and aqueous sodium bicarbonate solution. The extract is filtered and diluted with phosphate-buffered saline; and OTA is purified with an immunoaffinity column containing antibodies specific to OTA. The purified extract is dried, reconstituted, and quantified by HPLC with fluorescence detection. Twenty laboratories from 13 European Union member states, Uruguay, Turkey, and the United States of America participated in this study. The study was evaluated according to internationally accepted guidelines. The method performance characteristics can be summarized as follows: over a working range of 7.7 to 141 microg/kg OTA, the mean recoveries were 87% for licorice root and 84-88% for licorice extracts; and the RSDs for reproducibility ranged from 10 to 17% and from 11 to 22% in licorice extracts and licorice root, respectively. The method was found to be fit-for-purpose and to fulfill legal requirements as set in EC Regulation No. 401/2006.
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 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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".