Ultra trace simultaneous determination of 50 polycyclic aromatic hydrocarbons in biota using pMRM GC-MS/MS
Bibliographic record
Abstract
A saponification extraction method with gas chromatography pseudo-MRM (pMRM) mass spectrometry detection was developed for the determination of 50 total polycyclic aromatic hydrocarbons (TPAH50, a combination of parent and alkylated homologues) in biota. The method was aimed at monitoring and identification of potential TPAH contaminants in bitumen impacted environments. Alkylated PAHs were determined by multi-level, quantitative calibration using parent PAHs. The developed and thoroughly validated method required only one injection for TPAH50 analysis which represents significant saving of time and expensive authentic alkylated standards. The current method was tested with certified reference mussel tissue NIST 1974c and performed well. In a comparison study, the method reached a limit of quantitation (LOQ) for the TPAH50 between 0.1 and 0.2 ng g−1, while the QuEChERs enhanced matrix removal – lipid (EMR) kit produced by Agilent showed an LOQ of 5–10 ng g−1. The current method relied on response factors (RF) for the quantitation of alkylated PAHs determined against parent PAHs. These RFs were shown to be stable and consistent over the course of 1 year, during which over 200 routine environmental biota monitoring samples were analyzed. The environmental biota monitoring samples analyzed include muscle, carcass and liver, with an average total PAH50 concentration of 13, 90 and 135 ng g−1, respectively. Results show significant differences in the distributions of 1 ringed, 2 ringed, 3 ringed, 4 ringed, and 5+ ringed TPAHs between the types of biota samples.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".