Decoupling CE and ESI for a more robust interface with MS
Bibliographic record
Abstract
An interface for CE-ESI-MS that decouples both the electrical and the solution flow rate requirements of the separation and ionization processes is presented. The interface uses a tapered and beveled stainless steel hollow needle surrounding the separation capillary terminus so that the inside of the electrode acts as the CE outlet vial and the outside tip acts as the electrospray emitter. No capillary pre-treatment is required, enabling the use of capillaries with any type of surface modification. A chemical modifier solution is introduced through a second capillary connected to the needle via a tee junction and can be used to improve the compatibility of the CE BGE with electrospray. The flow rate of modifier solution can be as low as 0.1 microL/min, much less than that in a typical sheath-flow interface, thus minimizing dilution of the CE effluent in order to maximize sensitivity. The presence of the modifier solution also allows the use of neutral-coated capillaries for protein analysis by CE-MS without using an assisting pressure, despite the absence of EOF under these conditions. The interface is easily integrated into a commercial CE instrument, such that all operations can be carried out by the automated controls. Compared with a commercial sheath-flow CE-MS interface operating under optimized conditions, LODs for amino acids were, on average, improved fivefold.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".