Correlation of product ion profiles with molecular structures of androgenic and anabolic steroids in ESI MS/MS
Bibliographic record
Abstract
Androgenic and anabolic steroids (AASs) are a class of chemical substances closely related to testosterone in molecular structure. They can be abused to enhance performances in human and equine athletes, and are banned by the sports authorities. To assist with method development for doping analyses of AASs, investigations were conducted to correlate their product ion profiles with the molecular structures. Although very similar in chemical structure, AASs generated noticeably different product ion profiles from collision-induced dissociation (CID). On the basis of both outlines of the product ion profiles and molecular structures, AASs studied were classified into six subclasses. In each subclass, the product ion profiles were identical or similar. However, the product ion profiles in one subclass were remarkably different from those in another. The classification reveals that the position and number of double bond(s) in conjugation with the 3-carbonyl group in the molecular structure of an AAS have significant effects on product ion profile. The presence or absence of the 19-methyl group in an AAS also has a remarkable influence on its product ion profile. A substitution in the A-, B- or D-ring of an AAS may cause a shift in mass value of the product ions. The correlation of product ion profiles with molecular structures of AASs has the implication that each AAS can be characterized by a combination of its [M + H](+) ion and product ion profile and as a result be identified with specificity. The classified product ion pattern may be useful in the identification of unknown AASs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".