Mass analysis with islands of stability with linear quadrupoles incorporating higher order multipole fields
Bibliographic record
Abstract
Mass analysis with islands of stability has been investigated with three linear quadrupole mass filters: two with 4% added hexapole fields constructed with equal diameter (quadrupole 4A) and unequal diameter (quadrupole 4B) rods, and a conventional round-rod quadrupole that has apparently been slightly damaged. Islands are formed by applying auxiliary quadrupole excitation. With the Mathieu parameter, a < 0, mass analysis with both quadrupoles with hexapole fields operated normally, i.e., without islands, gives only low resolution. A factor of 10 or more increase in resolution is possible with the use of stability islands. With a > 0, when quadrupole 4A is operated normally, peak shapes similar to that of a conventional quadrupole can be obtained at resolutions higher than 850. At lower resolutions, peaks are split. When quadrupole 4B is operated without islands, resolution up to 2000 is possible, but there are low mass tails and structure is formed on the peaks. With mass analysis with an island of stability, both quadrupoles 4A and 4B show peaks free of structure and without tails. Ion transmission is also improved with some operating conditions. With the conventional round-rod quadrupole, mass analysis with islands of stability increases the limiting resolution from 2500 to 4360. At a resolution of 2500, the transmission is increased by about two orders of magnitude. These results show that the use of islands of stability improves mass analysis with quadrupoles with distorted fields, and may, in the future, allow use of quadrupoles constructed with at least some lower mechanical tolerances.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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 | 0.000 |
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".