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Record W2122533917 · doi:10.1517/17425250902976862

Genetic variation in androgen disposition: implications in clinical medicine including testosterone abuse

2009· review· en· W2122533917 on OpenAlexfundno aff
Jenny J. Schulze, Anders Rane, Lena Ekström

Bibliographic record

VenueExpert Opinion on Drug Metabolism & Toxicology · 2009
Typereview
Languageen
FieldMedicine
TopicHormonal and reproductive studies
Canadian institutionsnot available
FundersCancerföreningen i StockholmWorld Anti-Doping Agency
KeywordsTestosterone (patch)AndrogenAndrogen deficiencyMedicineAnabolic-Androgenic SteroidsTestosterone replacementSubstance abuseAnabolismEndocrinologyInternal medicineHormonePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Testosterone replacement therapy in hypogonadal men has been used for > 60 years. The use of testosterone substitution is continuously growing and is given to aging men to improve the quality of life. Because testosterone use is associated with muscle strength enhancing effects, it has become a popular drug to abuse. Doping with anabolic steroids, such as testosterone, is a severe challenge to the vision, moral and ethics in sports and has also become a significant and increasing problem in society. OBJECTIVE: The primary aim of this review is to summarize and discuss the contribution of genetic components to inter-individual variation in androgen disposition. CONCLUSION: Genetic variation has a large impact on androgen disposition. This variation is of the utmost importance for the interpretation of doping test results and may modulate the effects of testosterone replacement therapy and testosterone doping.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.114
GPT teacher head0.438
Teacher spread0.323 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations19
Published2009
Admission routes1
Has abstractyes

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