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Record W3118393203 · doi:10.14309/crj.0000000000000518

Drug-Induced Liver Injury From Enobosarm (Ostarine), a Selective Androgen Receptor Modulator

2021· article· en· W3118393203 on OpenAlexaff
Harjot Bedi, Carl Hammond, David Sanders, Hui-Min Yang, Eric M. Yoshida

Bibliographic record

VenueACG Case Reports Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicHormonal and reproductive studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineLiver injuryAndrogen receptorAnabolismDrugTestosterone (patch)CholestasisAnabolic AgentsPharmacologyAndrogenBioinformaticsEndocrinologyInternal medicineBiologyHormoneProstate cancer

Abstract

fetched live from OpenAlex

Anabolic steroids are well-known to cause liver injury, which may manifest with jaundice and elevated liver enzymes. Selective androgen receptor modulators (SARMs) have been developed to enhance muscle bulk without the side effects associated with exogenous androgen steroids. We report a case of significant cholestatic liver injury associated with a SARM, ostarine (enobosarm), similar to that associated with anabolic steroids. Liver injury from SARMs has not been reported frequently, and we speculate that this may be seen more often as the consumption of SARMs increases in the athletic market.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.123
Threshold uncertainty score0.835

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.275
Teacher spread0.254 · 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 designCase report
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

Citations29
Published2021
Admission routes1
Has abstractyes

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