Adjustable Methacrylate Porous Monolith Polymer Layer Open Tubular Silica Capillary Microextraction for the Determination of Polycyclic Aromatic Hydrocarbons
Bibliographic record
Abstract
A novel adjustable porous polymer monolith layer open tubular silica capillary microextraction (PLOT-ME) device was fabricated by thermal polymerization of a poly(glycidylmethacrylate-co-ethylene glycol dimethacrylate) (GMA-co-EDMA) polymer film (∼20 µm) within a 250 µm internal diameter silica capillary initiated with 4,4′-azobis(4-cyanopentanoyl chloride). The polymer film thickness and morphology were controlled by the polymerization time and temperature. The length of the microextraction platform immersed in the sample was adjusted by the sample concentration and sample matrix. Furthermore, since the microextraction platform performance typically degraded with use, the PLOT-ME device affords a new microextraction zone that may be exposed by cleaving off the end. This ability significantly reduces the cost of microextraction for academic and research environments. The performance of the PLOT-ME device was tested for microextraction of polycyclic aromatic hydrocarbons (PAHs): naphthalene, 2,6-dimethylnaphthalene, anthracene, 9-methylanthracene, and phenanthrene in aqueous media. Linear calibration curves for the PAHs were obtained with correlation coefficients near unity and relative standard deviations from 2 to 20% for PAH standards from 100 to 0.1 µg/L. The limits of detection for the PAHs were between 0.02 and 0.06 µg/L, while the recoveries were from 97 to 104% in lake water. The precision between different PLOT-ME devices was 11%.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".