Highly sensitive and selective analysis of urinary steroids by comprehensive two-dimensional gas chromatography combined with positive chemical ionization quadrupole mass spectrometry
Bibliographic record
Abstract
Comprehensive two dimensional gas chromatography (GC × GC) provides greater separation space than conventional GC. Because of fast peak elution, a time of flight mass spectrometer (TOFMS) is the usual structure-specific detector of choice. The quantitative capabilities of a novel GC × GC fast quadrupole MS were investigated with electron ionization (EI), and CH(4) or NH(3) positive chemical ionization (PCI) for analysis of endogenous urinary steroids targeted in anti-doping tests. Average precisions for steroid quantitative analysis from replicate urine extractions were 6% (RSD) for EI and 8% for PCI-NH(3). The average limits of detection (LODs) calculated by quantification ions for 12 target steroids spiked into steroid-free urine matrix (SFUM) were 2.6 ng mL(-1) for EI, 1.3 ng mL(-1) for PCI-CH(4), and 0.3 ng mL(-1) for PCI-NH(3), all in mass scanning mode. The measured limits of quantification (LOQs) with full mass scan GC × GC-qMS were comparable with the LOQ values measured by one-dimensional GC-MS in selected ion monitoring (SIM) mode. PCI-NH(3) yields fewer fragments and greater (pseudo)molecular ion abundances than EI or PCI-CH(4). These data show that a benchtop GC × GC-qMS system has the sensitivity, specificity, and resolution to analyze urinary steroids at normal urine concentrations, and that PCI-NH(3), not currently available on most GC × GC-TOFMS instruments, is of particular value for generation of structure-specific ions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".