Determination of veterinary pharmaceuticals in poultry litter and soil by methanol extraction and liquid chromatography-tandem mass spectrometry
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
Pharmaceuticals are emerging contaminants with potential risks to the environment and human health. A liquid chromatography-tandem mass spectrometry (LC-MS-MS) method was developed for determination of the antimicrobials virginiamycin, monensin, salinomycin, narasin and nicarbazin in poultry litter and soil. This method involves methanol extraction and clean-up of extracts through glass microfibre filters, introduction of the extracts and separation of compounds on a Zorbax Eclipse XDB C8 column, and compound detection in a Quattro Micro Micromass spectrometer. For litter samples, Method Detection Limits ranged from 0.1-0.6 microg Kg(-1), while Limits of Quantitation (LOQs) were 2, 1, 0.4, 1 and 2 microg Kg(-1) for virginiamycin, monensin, salinomycin, narasin and nicarbazin, respectively. For soil samples calculated LOQs were 2, 3, 1, 1, and 1 microg Kg(-1) for virginiamycin, monensin, salinomycin, narasin and nicarbazin, respectively. Application of the LC-MS-MS method for detection of veterinary pharmaceuticals in litter collected from commercial poultry farms showed that compounds were present at concentrations ranging from 10-11,000 microg Kg(-1).
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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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