Structure, Anion, and Solvent Effects on Cation Response in ESI-MS
Bibliographic record
Abstract
The abundance of an ion in an electrospray ionization mass spectrum is dependent on many factors beyond just solution concentration. Even in cases where the analytes of interest are permanently charged (under study here are ammonium and phosphonium ions) and do not rely on protonation or other chemical processes to acquire the necessary charge, factors such as cation structure, molecular weight, solvent, and the identity of the anion can affect results. Screening of a variety of combinations of cations, anions, and solvents provided insight into some of the more important factors. Rigid cations and anions that conferred high conductivity tended to provide the highest responses. The solvent that most closely reflected actual solution composition was acetonitrile, while methanol, acetonitrile/water, and dichloromethane produced a higher degree of discrimination between different ions. Functional groups that had affinity for the solvent tended to depress response. These observations will provide predictive power when accounting for analytes that for reasons of high reactivity can not be isolated.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".