Electrospray tandem mass spectrometric analysis of novel synthetic quinoxalinone derivatives
Bibliographic record
Abstract
Electrospray ionization tandem mass spectrometry (ESI-MS/MS) using a hybrid QqToF-MS/MS instrument has aided the structural characterization and differentiation of a novel series of medicinal synthetic 1-N-glycoside-quinoxalinone derivatives. These derivatives 7 and 8 are formed by an amino bond between the cyclic N-1 of the quinoxaline moiety and the C-6 position of a fully protected methyl or allyl alpha-D-mannofuranoside 3 and 4, and subsequent deprotection of the mannopyranoside moiety. In general the novel synthetic quinoxaline derivatives afforded the protonated molecules in ESI. The breakdown routes of the protonated molecules were rationalized by conducting low-energy CID-MS/MS analyses. In addition, re-confirmation of the various established fragmentation routes was achieved by conducting a series of ESI-CID-QqTof-MS/MS product ion scans on various selected precursor ions, which were initiated by CID in the atmospheric pressure/vacuum interface using a higher declustering potential. ESI-QqToF-MS/MS analysis has proven to be a specific and very sensitive method for the structural identification in the gas phase of these novel glycoquinoxalinamine derivatives.
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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".