Development of a Branched Radio-Frequency Ion Trap for Electron Based Dissociation and Related Applications
Bibliographic record
Abstract
Collision-induced dissociation (CID) is the most common tool for molecular analysis in mass spectrometry to date. However, there are difficulties associated with many applications because CID does not provide sufficient information to permit details of the molecular structures to be elucidated, including post-translational-modifications in proteomics, as well as isomer differentiation in metabolomics and lipidomics. To face these challenges, we are developing fast electron-based dissociation devices using a novel radio-frequency ion trap (i.e., a branched ion trap). These devices have the ability to perform electron capture dissociation (ECD) on multiply protonated peptide/proteins; in addition, the electron impact excitation of ions from organics (EIEIO) can be also performed on singly charged molecules using such a device. In this article, we review the development of this technology, in particular on how reaction speed for EIEIO analyses on singly charged ions can be improved. We also overview some unique, recently reported applications in both lipidomics and glycoproteomics.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".