The Chemistry of Paper in Paper Spray Ionization Mass Spectrometry
Bibliographic record
Abstract
There are many rapidly evolving technologies that use simple papers as a surface for chemical reactions and detection of molecules. One example of this application is the use of paper as a surface for ionization and introduction of compounds into mass spectrometry. The current work was designed to investigate mechanisms of interaction between the paper and analytes using mass spectrometry as the detection instrument. Standard compounds with different sizes were used in this study. Factors investigated include the effects of the paper geometry (5 mm) and position (tp=90º) were found to be optimal. The role of atmospheric water and the effects of paper porosity were affected the signals of the tested compounds. Investigations of the interaction of standard solutions with the paper surface indicated that atmospheric water is required for ionization. Up to three water molecules were detected in association with the analytes indicating that the presence of some water is required. In addition, this study showed the potential of silicon dioxide nanoparticles for eluting the standards compound from the paper surface. The impact of trace elements in the commercial papers and the interactions between the paper cellulose with different classes of analytes was investigated.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.008 | 0.003 |
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".