Equilibrium in-fiber standardization method for determination of sample volume by solid phase microextraction
Bibliographic record
Abstract
This paper describes an in-fiber standardization method by Solid Phase Microextraction (SPME) for the determination of a sample volume. After loading a specific amount of standard, the volumetric standard, on a PDMS-coated fiber (n(0)), the fiber was exposed in the headspace of sample vials containing different volumes of water. The amount of standard that remained on the fiber after equilibrium (n(f)), which was determined with gas chromatography/mass spectrometry (GC/MS), depends on the volume of the sample. Naphthalene, 1-methylnaphthalene, 2-methylnaphthalene, 1-ethylnaphthalene, and 2-ethylnaphthalene were chosen as volumetric standards based on theoretical calculations. The effect of loading time, exposure time, and exposure temperature were investigated. The effect of the matrix was also studied, analyzing both water and wine samples. Precision and accuracy of the method were obtained for each standard in both water and wine. The partition coefficients of the compounds between the fiber and the sample (K(fs)) and between the headspace and the sample (K(hs)) were obtained by plotting n(0)/n(f)versus sample volume.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".