Rapid and Sensitive Determination of Residues of Triphenylmethane Dyes and Their Metabolites in Animal Tissues by LC–MS/MS
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
This article describes a fast, sensitive, selective, and robust method for determining triphenylmethane dyes and their metabolites in animal tissue samples by liquid chromatography with tandem mass spectrometry (LC–MS/MS). The separation of analytes from matrix-interfering components was performed using a C18 column with a mobile phase composition of water and methanol containing 0.1% formic acid and 5 mM ammonium formate as additives in both phases. To minimize sample matrix effects and analyte loss during sample preparation, extracted-matrix calibration in combination with isotope dilution was used for analyte quantification. There were two MS/MS transitions selected for each analyte for analyte confirmation, further enhancing the method’s selectivity and accuracy. The method was validated using salmon and chicken tissue samples.
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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 | 0.000 |
| 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) | 0.000 | 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