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Record W2018391602 · doi:10.1002/jms.1803

Correlation of product ion profiles with molecular structures of androgenic and anabolic steroids in ESI MS/MS

2010· article· en· W2018391602 on OpenAlexfundno aff
Fuyu Guan, Cornelius E. Uboh, Lawrence R. Soma, Youwen You, Ying Liu, Xiaoqing Li

Bibliographic record

VenueJournal of Mass Spectrometry · 2010
Typearticle
Languageen
FieldMedicine
TopicHormonal and reproductive studies
Canadian institutionsnot available
FundersWorld Anti-Doping AgencyUniversity of Pennsylvania
KeywordsChemistryIonDissociation (chemistry)Anabolic-Androgenic SteroidsAnabolismOrganic chemistryBiochemistry

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.431
Threshold uncertainty score0.268

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.005
GPT teacher head0.239
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2010
Admission routes1
Has abstractyes

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