Electrospray ionization suppression, a physical or a chemical phenomenon?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Mass spectrometry is a powerful qualitative and quantitative analytical technique that has been introduced in many bioanalytical and research laboratories in the last 10 years. The combination of HPLC with tandem MS yields a particularly powerful tool and it is now the method of choice for the analysis drugs, metabolites, biomarkers and proteins. However, HPLC-MS methods are not completely without problems that can compromise the quality of the results. An important phenomenon that can affect the quantitative performance of a mass detector is ion suppression. In this study, we measured the influence of the observed current (I) vs signal intensity and the variation of the observed current (I) when analyzing biological samples. Our experiment suggests that, despite the fact that it is possible for other chemicals to compete for protons in the droplets, the increase in the observed current (I) during the signal suppression is important and indicates that the conductivity of the liquid increases significantly. The salts and the charged species influence the conductivity and the surface tension of the droplets and modify the equilibrium between the two main forces involved during the electrospray process, resulting in an erratic spray behavior.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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 it