SPME in Environmental Analysis: Biotransformation Pathways
Bibliographic record
Abstract
Solid-phase microextraction (SPME) is an organic solvent-free sample preparation tool suitable for direct adsorption of analytes from the headspace or the aqueous phase of a matrix followed by desorption into a gas chromatograph (GC) or high-performance liquid chromatograph (HPLC) for subsequent analysis. The SPME technique is designed to accommodate the use of fibers coated with different polymers suitable for the extraction of chemicals with varied hydrophobic and polar properties. Also, the technique can minimize interference from other artefacts associated with complex samples, such as those encountered in biological matrices or reaction mixtures. The preceding characteristics of SPME make the technique suitable for real-time measurements of intermediate reaction products and, thus, able to provide insight into the fate of target chemicals and their degradation pathways. In the present article, the current state of knowledge on the use of SPME-GC and SPME-HPLC in the determination of frequently encountered environmental chemicals and their (bio)transformation pathways are critically reviewed. Future opportunities of SPME in real time in situ process monitoring such as the use of agricultural feed stocks to bio-based industrial products termed henceforth "process analytical chemistry" are also discussed.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".