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Record W2084650359 · doi:10.2147/oajsm.s11626

Growth hormone doping: a review

2011· review· en· W2084650359 on OpenAlexfundno aff
Peter H. Sönksen, Richard I. G. Holt, Ioulietta Erotokritou‐Mulligan

Bibliographic record

VenueOpen Access Journal of Sports Medicine · 2011
Typereview
Languageen
FieldMedicine
TopicGrowth Hormone and Insulin-like Growth Factors
Canadian institutionsnot available
FundersWorld Anti-Doping Agency
KeywordsAthletesGrowth hormonePerformance enhancementMedicineIntensive care medicineHormonePsychologyPhysical therapyPhysical medicine and rehabilitationEndocrinology

Abstract

fetched live from OpenAlex

The use of growth hormone (GH) as a performance enhancing substance was first promoted in lay publications, long before scientists fully acknowledged its benefits. It is thought athletes currently use GH to enhance their athletic performance and to accelerate the healing of sporting injuries. Over recent years, a number of high profile athletes have admitted to using GH. To date, there is only limited and weak evidence for its beneficial effects on performance. Nevertheless the "hype" around its effectiveness and the lack of a foolproof detection methodology that will detect its abuse longer than 24 hours after the last injection has encouraged its widespread use. This article reviews the current evidence of the ergogenic effects of GH along with the risks associated with its use. The review also examines methodologies, both currently available and in development for detecting its abuse.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.743
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0100.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0040.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.192
GPT teacher head0.454
Teacher spread0.262 · 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.

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
Published2011
Admission routes1
Has abstractyes

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