Ultraviolet photodissociation of protonated pharmaceuticals in a pressurized linear quadrupole ion trap
Bibliographic record
Abstract
Ultraviolet photodissociation (UVPD) was evaluated as a technique for generating ion fragmentation information that is alternative and/or complementary to the information obtained by collision-induced dissociation (CID). Ions trapped in a pressurized linear ion trap were dissociated using a 355 nm or a 266 nm pulsed laser. Comparisons of UVPD and CID spectra using a set of aromatic chromophore-containing compounds (desmethyl bosentan, haloperidol, nelfinavir) demonstrated distinct characteristic fragmentation patterns resulting from photodissociation. The wavelength of light and the pressure of the buffer gas in the UVPD cell are important parameters that control fragmentation pathways. The wavelength effect is related to the absorption cross section, location of the chromophore and the energy carried by one photon. Thus, UV irradiation wavelength affects fragmentation pathways as well as the fragmentation rate. The pressure effect can be explained by collisional quenching of 'slow' fragmentation pathways. We observed that higher pressure of the buffer gas during UVPD experiments highlights unique fragment ions by suppressing slow fragmentation pathways responsible for CID-like fragmentation patterns.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".