Identification of degradants of a complex alkaloid using NMR cryoprobe technology and ACD/structure elucidator
Bibliographic record
Abstract
Abstract Identification of degradants of pharmaceuticals is a necessary challenge of the drug development process following the subjection of candidate molecules to a variety of physico‐chemical stresses. It would be desirable to be able to conduct such studies on a minimal amount of material. As a prototypical study, the isolation and identification of degradants of a sample of the complex indoloquinoline alkaloid, cryptospirolepine, was undertaken after prolonged storage in DMSO solution using a combination of cryogenic NMR probe technology and CASE (Computer‐Assisted Structure Elucidation) programs. None of the starting alkaloid remained after storage; a chromatogram of the DMSO solution demonstrated the presence of >25 components in the mixture. The two most abundant degradation products were identified as the known alkaloid cryptolepinone (∼35%) and an unprecedented rearrangement product, DP‐2, (∼16%).
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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 | 0.000 | 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".