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Record W4386532223 · doi:10.1177/17557380231198829

Androgenic anabolic steroid abuse

2023· article· en· W4386532223 on OpenAlexaff
Dr Emilia Robinson, Dr Raju Haque, Dr Aline Eggink

Bibliographic record

VenueInnovAiT Education and inspiration for general practice · 2023
Typearticle
Languageen
FieldMedicine
TopicHormonal and reproductive studies
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsAnabolismAnabolic steroidDrugs of abuseTestosterone (patch)Adverse effectSteroid useSubstance abuseMedicinePsychologyPsychiatryDrugEndocrinologyPharmacologyInternal medicine

Abstract

fetched live from OpenAlex

Androgen anabolic steroid abuse is a broad term describing the use of structural derivatives of testosterone with the aim to increase body mass and muscle size, or to enhance athletic performance. These drugs are typically used in large doses, much higher than would be prescribed for the treatment of medical conditions. This use of steroids is illegal and can lead to multiple adverse effects including cardiovascular, hepatic, metabolic and psychological issues. Many patients abusing steroids will not typically disclose this information when presenting to their GP. This article aims to help raise awareness of signs and symptoms of abuse, as well as highlight the common long-term risks and discuss a GP’s role in managing these complex scenarios.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.787
Threshold uncertainty score0.335

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.033
GPT teacher head0.371
Teacher spread0.338 · 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 designNot applicable
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

Citations0
Published2023
Admission routes1
Has abstractyes

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