The importance of both charge exchange and proton transfer in the analysis of polycyclic aromatic compounds using atmospheric pressure chemical ionization mass spectrometry
Bibliographic record
Abstract
The response of atmospheric pressure chemical ionization (APCI) mass spectrometry to selected polycyclic aromatic compounds (PACs) was examined in a Micromass Quattro atmospheric pressure ion source as a function of both solvents and source gases. Typical PACs found in petroleum samples were represented by mixtures of naphthalene, fluorene, phenanthrene, pyrene, fluoranthene, chrysene, triphenylene, perylene, carbazole, dibenzothiophene, and 9-phenanthrol. A large range of different gases in the APCI source was studied, with emphasis on nitrogen, air, and carbon dioxide. Solvents used included water-acetonitrile, acetonitrile, dichloromethane, and hexanes. The signal responses were dependent on both the gases and solvents used, as was the ionization mechanism, as indicated by the degree of protonation with respect to the level of charge exchange. The combination of carbon dioxide in the nebulizer gas stream with nitrogen in the other streams gave a three- to fourfold better sensitivity than using nitrogen alone for both test mixtures and for complex 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".