Quindolinocryptotackieine: the elucidation of a novel indoloquinoline alkaloid structure through the use of computer‐assisted structure elucidation and 2D NMR
Bibliographic record
Abstract
Abstract Numerous indoloquinoline alkaloid structures have been identified from extracts of the West African plant Cryptolepis sanguinolenta. Recently, through the use of 2D NMR methods and cryogenic NMR probe technology in conjunction with computer‐assisted structure elucidation (CASE) methods, the structures of some chemical degradation products of this family of alkaloids have also been reported. We now report the characterization of a novel indoloquinoline dimeric alkaloid, quindolinocryptotackieine, through the extensive utilization of CASE methods. The NMR data presented here were collected over a decade earlier before the elucidation of the structure was possible, since manual analysis did not present a conclusive structure, whereas CASE produced a series of structures from which the structure could be verified. The original mass spectrometric (MS) data collected for the sample were problematic. Contemporary MS data were instead recollected from remaining small quantities of this alkaloid using modern instrumentation. The re‐collected data gave a usable molecular ion and several key fragment ions that were diagnostically useful. Copyright © 2003 John Wiley & Sons, Ltd.
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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".