Method for determination of stable carbon isotope ratio of methylnitrophenols in atmospheric particulate matter
Bibliographic record
Abstract
Abstract. A technique for the measurement of the stable isotope ratio of methylnitrophenols in atmospheric particulate matter is presented. Atmospheric samples from rural and suburban areas were collected for evaluation of the procedure. Particulate matter was collected on quartz fibre filters using dichotomous high volume air samplers. Methylnitrophenols were extracted from the filters using acetonitrile. The sample was then purified using a combination of high-performance liquid chromatography and solid phase extraction. The final solution was then divided into two aliquots. To one aliquot, a derivatising agent, Bis(trimethylsilyl)trifluoroacetamide, was added for Gas Chromatography-Mass Spectrometry analysis. The second half of the sample was stored in a refrigerator. For samples with concentrations exceeding 1 ng μl−1, the second half of the sample was used for measurement of stable carbon isotope ratios by Gas Chromatography-Isotope Ratio Mass Spectrometry. The procedure described in this paper provides a method for the analysis of methylnitrophenols in atmospheric particulate matter at concentrations as low as 0.3 pg m−3 and for stable isotope ratios with an accuracy of better than ±0.5‰ for concentrations exceeding 100 pg m−3. In all atmospheric particulate matter samples analysed, 2-methyl-4-nitrophenol was found to be the most abundant methylnitrophenol, with concentrations ranging from the low pg m−3 range in rural areas to more than 200 pg m−3 in some samples from a suburban location.
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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 | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".