Determination and confirmation of selective estrogen receptor modulators (SERMs), anti-estrogens and aromatase inhibitors in bovine and porcine urine using UHPLC-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
Selective estrogen receptor modulators (SERMs), anti-estrogens and aromatase inhibitors are prohibited in human sports doping. However, they also present a risk of being used illegally in animal husbandry for fattening purposes. A method was developed and validated using UHPLC-MS/MS for the determination and confirmation of SERMs, anti-estrogens and aromatase inhibiters in bovine and porcine urine. This method was used in a survey of more than 200 bovine and porcine urine samples from Dutch farms. In 18 out of 103 porcine urine samples (17%) and two out of 114 bovine samples (2%) formestane, an aromatase inhibitor, was detected. None of the other compounds was detected. From human doping control it is known that formestane can, in some cases, be of natural origin. Analyses of reference samples from untreated bovine and porcine animals demonstrated the presence of formestane in bovine animals, but not yet in porcine animals. Future research will focus on whether the detected formestane in porcine and bovine urine is from endogenous or exogenous origin, using GC-c-IRMS.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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