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Record W2929616584 · doi:10.21037/tau.2019.01.16

Can serum 17-hydroxyprogesterone and insulin-like factor 3 be used as a marker for evaluation of intratesticular testosterone?

2019· review· en· W2929616584 on OpenAlexaff
Ashaka Patel, Premal Patel, Joshua Bitran, Ranjith Ramasamy

Bibliographic record

VenueTranslational Andrology and Urology · 2019
Typereview
Languageen
FieldMedicine
TopicSperm and Testicular Function
Canadian institutionsMcMaster University
Fundersnot available
KeywordsTestosterone (patch)BiomarkerInfertilityInternal medicineEndocrinologyHormoneMedicineSpermatogenesisBiologyBiochemistryPregnancy

Abstract

fetched live from OpenAlex

Serum testosterone values vary considerably with little correlation to intratesticular testosterone (ITT). ITT is approximately ~100 times that of serum testosterone and is critical for spermatogenesis. Unfortunately, the only method to accurately measure ITT is invasive testicular aspiration and therefore is not performed routinely. The identification of a serum biomarker for ITT would allow serial monitoring during hormonal manipulation and the ability to assess the effectiveness of a male contraceptive agent. Prior studies have evaluated several serum biomarkers for their ability to accurately reflect ITT with data supporting 17-hydroxyprogesterone (17-OHP) and insulin-like factor 3 (INSL3) as a potential marker. Because evaluation of serum 17-OHP is readily available through commercial laboratories, in this review, we present the evidence for 17-OHP and how it can play a pivotal role in the management of male infertility.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.952
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0010.000
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 head0.080
GPT teacher head0.337
Teacher spread0.258 · 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 designOther design
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

Citations17
Published2019
Admission routes1
Has abstractyes

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