Validation of a new screening, determinative, and confirmatory multi‐residue method for nitroimidazoles and their hydroxy metabolites in turkey muscle tissue by liquid chromatography‐tandem mass spectrometry
Bibliographic record
Abstract
A new and sensitive multi-residue method (MRM) with detection by LC-MS/MS was developed and validated for the screening, determination, and confirmation of residues of 7 nitroimidazoles and 3 of their metabolites in turkey muscle tissues at concentrations ≥ 0.05 ng/g. The compounds were extracted into a solvent with an alkali salt. Sample clean-up and concentration was then done by solid-phase extraction (SPE) and the compounds were quantified by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The characteristic parameters including repeatability, selectivity, ruggedness, stability, level of quantification, and level of confirmation for the new method were determined. Method validation was achieved by independent verification of the parameters measured during method characterization. The seven nitroimidazoles included are metronidazole (MTZ), ronidazole (RNZ), dimetridazole (DMZ), tinidazole (TNZ), ornidazole (ONZ), ipronidazole (IPR), and carnidazole (CNZ). It was discovered during the single laboratory validation of the method that five of the seven nitroimidazoles (i.e. metronidazole, dimetridazole, tinidazole, ornidazole and ipronidazole) and the 3 metabolites (1-(2-hydroxyethyl)-2-hydroxymethyl-5-nitroimidazole (MTZ-OH), 2-hydroxymethyl-1-methyl-5-nitroimidazole (HMMNI, the common metabolite of ronidazole and dimetridazole), and 1-methyl-2-(2'-hydroxyisopropyl)-5-nitroimidazole (IPR-OH) included in this study could be detected, confirmed, and quantified accurately whereas RNZ and CNZ could only be detected and confirmed but not accurately quantified.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".