Behaviour of tetraalkylammonium ions in high‐field asymmetric waveform ion mobility spectrometry
Bibliographic record
Abstract
High-field asymmetric waveform ion mobility spectrometry (FAIMS) is an ion-filtering technique recently adapted for use with liquid chromatography/mass spectrometry (LC/MS) to remove interferences during analysis of complex matrices. This is the first systematic study of a series of singly charged tetraalkylammonium ions by FAIMS-MS. The compensation voltage (CV) is the DC offset of the waveform which permits the ion to emerge from FAIMS and it was determined for each member of the series under various conditions. The electrospray ionization conditions explored included spray voltage, vaporizer temperature, and sheath and auxiliary gas pressure. The FAIMS conditions explored included carrier gas flow rate, electrode temperature and composition of the carrier gas. Optimum desolvation was achieved using sufficient carrier gas (flow rate > or = 2 L/min) to ensure stable response. Low-mass ions (m/z 100-200) are more susceptible to changes in electrode temperature and gas composition than high mass ions (m/z 200-700). As a result of this study, ions are reliably analyzed using standard FAIMS conditions (dispersion voltage -5000 V, carrier gas flow rate 3 L/min, 50% helium/50%nitrogen, inner electrode temperature 70 degrees C and outer electrode temperature 90 degrees C). Variation of FAIMS conditions may be of great use for the separation of very low mass tetraalkylammonium (TAA) ions from other TAA ions. The FAIMS conditions do not appear to have a major effect on higher mass ions.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.001 | 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".