Quadrupole mass filters with added hexapole fields
Bibliographic record
Abstract
Conventional mass analysis has been investigated experimentally with six quadrupole mass filters with added hexapole fields; three with added hexapole fields of 4%, 8% and 12% with equal diameter rods, and three with added hexapole fields of 4%, 8% and 12% with unequal diameter rods to remove an added octopole field. Compared with conventional quadrupoles, these rod sets have very large field distortions. With the positive resolving dc applied to the y rods (Mathieu parameter a(x) < 0) only low resolution (10-100) and low transmission are seen. With the polarity reversed (a(x) > 0) much higher resolution (> or = 1000) and transmission are possible. Increasing the magnitude of the added hexapole field decreases the limiting resolution at m/z 609. Removing the added octopole field increases the limiting resolution. In some cases structure is formed on the peaks. For a given scan line slope, U/V(rf), the resolution decreases as the amplitude of the added hexapole field increases. These results are consistent with changes to the stability diagrams, calculated here. With a(x) > 0, adding a hexapole field causes the x stability boundary to move outward with all rod sets. With a(x) < 0, the boundaries become diffuse and the tip of the stability diagram becomes rounded, limiting the resolution to ca. 10-100. Where comparisons are possible, experiments show the rod sets with added hexapole fields have transmission 10-300 times less than a conventional quadrupole. Thus these quadrupoles are less useful for mass analysis than conventional quadrupoles. However, it is surprising, given the highly distorted fields, that some of the quadrupoles give resolution of 1000 or more.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".