Determination of chlortetracycline in swine plasma by LC‐ESI/MS/MS
Bibliographic record
Abstract
A rapid, selective and sensitive method has been developed for the determination of chlortetracycline in swine plasma by LC-ESI/MS/MS. The method consists of a protein precipitation extraction for sample preparation and liquid chromatography ionspray tandem mass spectrometry for analysis. The plasma samples were extracted with acetonitrile and the supernatants were analyzed using an LC-ESI/MS/MS instrument. Separation was achieved using a C(8) analytical column and an isocratic mobile phase composed of 70:30 acetonitrile:0.5% formic acid in water at a flow rate of 500 microL/min. A linear (weighted 1/concentration) relationship was used to perform the calibration over an analytical range 20--2000 ppb (ng/mL). The intra-batch precision and accuracy at LLOQ, medium and high concentrations were 9.0, 11.3 and 9.9% and 97.7, 100.3 and 98.4%, respectively, and the inter-batch precision and accuracy at LLOQ, medium and high concentrations were 9.1, 8.4 and 7.4% and 95.1, 102.1 and 97.1%, respectively. This LC-ESI/MS/MS method for the determination of chlortetracycline in swine plasma has been proven to be within generally accepted criteria used for bioanalytical assay.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".