Peak structure with a quadrupole mass filter operated in the first stability region
Bibliographic record
Abstract
Rationale In the development of commercial quadrupole mass spectrometers, there is an interest in understanding the factors that affect the transmission and peak shape of ions passing through the mass filter. These include the ion collection effects of the ion optics that lead to the presence of a peak structure. Methods The peak structure can be observed by increasing the ion's axial kinetic energy and reducing the mass step size in a mass spectrum. The calculation of the maxima in the peak structure can be achieved by first obtaining the Mathieu characteristic parameter β y from the scan lines for each mass. The ion's secular frequency, ω 0,y , along with the ion's transit time through the mass filter can then be used to calculate the location of the maxima in the peak structure. Results Experimentally, a peak structure has been observed for m/z 42, m/z 118 and m/z 622 in the Q1 scan mode of a triple quadrupole mass spectrometer. The peak structure has shown a dependency on the ion's axial kinetic energy, but, a mass independency with regard to the number of maxima is observed in the peak structure. In the Q3 scan mode, there is an absence of the peak structure due to the ion collection efficiency of the HED detection system. Conclusions Under the right conditions, the peak structure due to ion collection effects can be observed with a quadrupole mass filter operated in the Mathieu first stability region. The presence of the peak structure has been shown to depend upon the ion collection effects at the exit of the mass filter.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 0.001 |
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".