Enzymatic Assay for GHB Determination in Forensic Matrices
Bibliographic record
Abstract
Current procedures for the determination of gamma-hydroxybutyric acid (GHB) require time-consuming extraction and derivatization steps before chromatographic detection, making a high-throughput alternative desirable. Bühlmann Laboratories offers an enzymatic assay for the quantitative determination of GHB in urine and serum. We report the adaptation of this photometric assay to the Thermo Scientific MGC-240 analyzer and its use in the determination of GHB in forensic matrices including urine, whole blood and vitreous humour. Most matrices require only a brief centrifugation before analysis, while blood requires an additional protein precipitation step. A variety of cases (sexual assaults, impaired drivers and death investigations) have been analyzed alongside the gas chromatography-mass spectrometry (GC-MS) reference method. Correlation with the GC-MS has been found to be acceptable, with no false negatives and few false positives, although postmortem samples appear more prone to testing false positive than do antemortem samples. Simple sample preparation and high throughput allow for a significant reduction in analysis time relative to chromatographic methods. This assay is used as a screening method in our laboratory, with a quantitative GC-MS method serving for the confirmation of positive results. To our knowledge, this represents the first evaluation of an enzymatic assay for GHB in a forensic context.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".