Application of isotope dilution mass spectrometry: determination of ochratoxin A in the Canadian Total Diet Study
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
Analytical methods are generally developed and optimized for specific commodities. Total Diet Studies, representing typical food products 'as consumed', pose an analytical challenge since every food product is different. In order to address this technical challenge, a selective and sensitive analytical method was developed suitable for the quantitation of ochratoxin A (OTA) in Canadian Total Diet Study composites. The method uses an acidified solvent extraction, an immunoaffinity column (IAC) for clean-up, liquid chromatography-tandem mass spectrometry (LC-MS/MS) for identification and quantification, and a uniformly stable isotope-labelled OTA (U-[(13)C(20)]-OTA) as an internal recovery standard. Results are corrected for this standard. The method is accurate (101% average recovery) and precise (5.5% relative standard deviation (RSD)) based on 17 duplicate analysis of various food products over 2 years. A total of 140 diet composites were analysed for OTA as part of the Canadian Total Diet Study. Samples were collected at retail level from two Canadian cities, Quebec City and Calgary, in 2008 and 2009, respectively. The results indicate that 73% (102/140) of the samples had detectable levels of OTA, with some of the highest levels of OTA contamination found in the Canadian bread supply.
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.
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 | 0.001 |
| 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