Dynamic collision-induced dissociation (DCID) in a quadrupole ion trap using a two-frequency excitation waveform: II. Effects of frequency spacing and scan rate
Bibliographic record
Abstract
Dynamic CID of selected precursor ions is achieved by the application of a two-frequency excitation waveform to the end-cap electrodes during the mass instability scan of a quadrupole ion trap (QIT) mass spectrometer. This new method permits a shorter scanning time when compared with conventional on-resonance CID. When the excitation waveform consists of two closely-spaced frequencies, the relative phase-relationship of the two frequencies plays a critical role in the fragmentation dynamics. However, at wider frequency spacings (>10 kHz), these phase effects are diminished, while maintaining the efficacy of closely-spaced excitation frequencies. The fragmentation efficiencies and energetics of n-butylbenzene and tetra-alanine are studied under different experimental conditions and the results are compared at various scan rate parameters between 0.1 and 1.0 ms/Th. Although faster scan rates reduce the analysis time, the maximum observed fragmentation efficiencies rarely exceed 30%, compared with values in excess of 50% achieved at slower scan rates. The internal energies calculated from the simulations of n-butylbenzene at fast scan rates are approximately 4 eV for most experimental conditions, while at slow scan rates, internal energies above 5.5 eV are observed for a wide range of conditions. Extensive ITSIM simulations support the observation that slowing the scan rate has a similar effect on fragmentation as widening the frequency spacing between the two excitation frequencies. Both approaches generally enhance CID efficiencies and make fragmentation less dependent upon the relative phase angle between the excitation waveform and the ion motion.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| 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".