Stability of cyclopiazonic acid in solution
Bibliographic record
Abstract
Cyclopiazonic acid (CPA) is an important mycotoxin given its toxicity and prevalence in foods and feeds. There is tremendous interest in developing analytical methods that include CPA as part of a multi-residue mycotoxin routine, but there appears to be considerable difficulty in analysing it using liquid chromatography with electrospray ionisation tandem mass spectrometry (LC-MS/MS). During the development of a multi-residue method for mycotoxins including CPA, a number of issues were discovered under routine and common analytical conditions that have an impact on the determination of CPA, including: (1) at the ng/ml level CPA reacts with ambient oxygen from the headspace of the vial, an effect that decreases its concentration linearly; (2) CPA readily adsorbs to plastic in a reversible fashion; (3) CPA is acid hydrolysed with formic acid; (4) CPA reacts with the column stationary phase affecting chromatographic parameters; and (5) CPA presents significant carry-over issues. In an effort to find solutions to these problems we found that CPA can be protected from reacting with oxygen by adding 1 µg/ml ascorbic acid and that its carry-over can be reduced to a negligible level by injecting ammonia between injections of solutions containing CPA, even with formic acid in the mobile phase. Chromatographic conditions for CPA have been optimised in consideration of all of the aforementioned concerns.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".