MétaCan
Menu
Back to cohort
Record W2130855701

Varicocelectomy: microsurgical subinguinal technique is the treatment of choice.

2007· article· en· W2130855701 on OpenAlexaff
Armand Zini

Bibliographic record

VenuePubMed · 2007
Typearticle
Languageen
FieldMedicine
TopicSperm and Testicular Function
Canadian institutionsRoyal Victoria Hospital
Fundersnot available
KeywordsVaricoceleMedicineInfertilityFertilityMale infertilitySemen qualityPregnancy ratePopulationGynecologyUrologyPregnancySurgerySpermAndrologyBiology
DOInot available

Abstract

fetched live from OpenAlex

It is reported that 35% to 40% of infertile men have a palpable varicocele (dilated testicular veins), whereas the prevalence of a varicocele in the general male population is about 15%.1,2,3 Although varicoceles have been associated with impaired male fertility potential, it is also clear that a significant proportion of men with a varicocele (about 75%) are fertile.2,4,5 As such, a cause and effect relationship between varicocele and male infertility has not been conclusively established.6 The effect of varicocelectomy on male fertility is also controversial.6–10 Uncontrolled studies have generally shown improved semen quality and pregnancy outcome after surgery.11 On the other hand, the results of randomized controlled studies of varicocelectomy for clinical varicocele (only a few such studies are published) are equivocal.12–15 Despite the absence of clear evidence for a positive effect of varicocelectomy, many clinicians consider the data sufficient to support the practice of this surgery, and varicocele is the most commonly treated condition in men with infertility in North America.8 The benefit of varicocele repair must be balanced by the risk associated with the procedure itself. As such, it is important to select the procedure with the highest success and lowest complication rate. Also, it is important to consider assisted reproductive technologies (ARTs) as an alternative to varicocelectomy in infertile couples.16

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.477
Threshold uncertainty score0.194

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.022
GPT teacher head0.256
Teacher spread0.234 · 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 designObservational
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

Citations24
Published2007
Admission routes1
Has abstractyes

Explore more

Same venuePubMedSame topicSperm and Testicular FunctionFrench-language works237,207