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Record W2145626737 · doi:10.1097/med.0b013e328353732f

Evolving utility of sex hormone-binding globulin measurements in clinical medicine

2012· review· en· W2145626737 on OpenAlexafffund
Geoffrey L. Hammond, Tsung-Sheng Wu, Marc Simard

Bibliographic record

VenueCurrent Opinion in Endocrinology Diabetes and Obesity · 2012
Typereview
Languageen
FieldMedicine
TopicHormonal and reproductive studies
Canadian institutionsChild and Family Research InstituteUniversity of British Columbia
FundersCanadian Institutes of Health ResearchCanada Research Chairs
KeywordsSex hormone-binding globulinTestosterone (patch)BiomarkerInternal medicineEndocrinologyHormoneEndocrine systemBiologyAndrogenMedicineGenetics

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Sex hormone-binding globulin (SHBG) regulates the plasma levels and biological actions of the sex steroids: testosterone and estradiol. Advances in our understanding of how plasma SHBG levels are determined, and how SHBG functions, have provided insight into how SHBG should be used to assess the actions of its sex-steroid ligands, and as a biomarker of metabolic and endocrine abnormalities. RECENT FINDINGS: Plasma SHBG levels fluctuate throughout life in response to the changes in metabolic and physiologic states, and are altered by natural hormones and synthetic steroids. Interindividual differences in plasma SHBG levels and activity are also influenced by polymorphisms within the structural and regulatory regions of the SHBG gene. SUMMARY: Measurements of SHBG are widely used to predict plasma free testosterone levels in patients suffering from excess androgen exposures, but have broader utility in assessing the risk for endocrine diseases and clinical sequelae of the metabolic syndrome, namely, type 2 diabetes and cardiovascular disease. It is anticipated that new genetic and functional data regarding SHBG will reveal whether SHBG is simply a biomarker of these diseases or participants in their cause.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.432
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.260
GPT teacher head0.443
Teacher spread0.183 · 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 designObservational
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

Citations104
Published2012
Admission routes2
Has abstractyes

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