Fast screening of illicit drugs in beverages and biological fluids by direct coupling of thin film microextraction to dielectric barrier discharge ionization-mass spectrometry
Bibliographic record
Abstract
A direct and fast method for screening and quantification of illicit drugs in beverages and biological fluids was developed by using dielectric barrier discharge (DBD) as ionization technique, in combination with high-resolution mass spectrometry. Extraction of the targeted analytes was carried out with thin film microextraction (TFME) using ultrasound as agitation method. The targeted analytes were then thermally desorbed and introduced into the source without the need for any cryofocusing apparatus. The performance of this new analytical set up were compared to conventional TFME-TDU-GC/MS, showing enhanced linear dynamic range and lower limits of quantitation (low pg ml-1) achievable at the same extraction conditions (5 min extraction time). The performance of the method was tested in different beverages and body fluids, confirming its applicability for quantitative analysis of the targeted drugs in complex samples.
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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) | 0.000 | 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) | 0.001 | 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".