Rapid and sensitive differentiation of anomers, linkage, and position isomers of disaccharides using High-Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS)
Bibliographic record
Abstract
A challenging aspect of structural elucidation of carbohydrates is gaining unambiguous information for anomers, linkage, and position isomers. Such isomers with identical mass can't be easily distinguished in mass spectrometry and a separation step is required prior to mass spectrometry identification. In our laboratory, gas-phase separation and differentiation of anomers, linkage, and position isomers of disaccharides was achieved using High-Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS). The FAIMS method responds to changes in ion mobility at high field rather than absolute values of ion mobility, and was shown to provide efficient separation and identification of disaccharide isomers at high sensitivity. Separation of analyzed disaccharide isomers can be accomplished at low nM level in a matter of seconds without sample purification or fractionation. Capability for examining a large population of ionic species of disaccharides by this method allowed for correlating structural details of disaccharide isomers with their separation properties in FAIMS. Results for disaccharide isomers indicate that this method could be applied to a larger group of carbohydrates.
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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 | 0.001 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".