Detection of multiple steroidal compounds in synthetic urine using comprehensive gas chromatography-mass spectrometry (GC×GC-MS) combined with a molecularly imprinted polymer clean-up protocol
Bibliographic record
Abstract
A method capable of screening for multiple steroids in urine has been developed, using a series of twelve structurally similar, and commercially relevant compounds as target analytes. A molecularly imprinted solid phase extraction clean-up step was used to make the sample suitable for injection onto a GC×GC-MS setup. Significant improvements compared to a commercially available C-18 material were observed. Each individual steroid was able to be separated and identified, using both the retention profile and diagnostic fragmentation ion monitoring abilities of the comprehensive chromatographic-mass spectrometry method. Effective LODs of between 11.7 and 27.0 pg were calculated for individual steroids, effectively equivalent to concentration levels of between 0.234 and 0.540 ng mL(-1) in urine, while the application of multiple screen was demonstrated using a 10 ng mL(-1) mixed sample. The nature of this study also removes the need for sample derivitisation which speeds up the screening process.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".