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Record W1971778703 · doi:10.1097/gco.0b013e32832947c2

Cytogenetic risks in chromosomally normal infertile men

2009· review· en· W1971778703 on OpenAlexaff
Helen G. Tempest, Renée H. Martin

Bibliographic record

VenueCurrent Opinion in Obstetrics & Gynecology · 2009
Typereview
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsIntracytoplasmic sperm injectionAneuploidyInfertilityMale infertilitySpermMedicineUnexplained infertilityGynecologyGenetic testingAndrologyObstetricsBiologyGeneticsPregnancyChromosomeInternal medicineGene

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Infertility is a growing problem that affects a surprisingly high number of couples (15%) of which the causes often remain 'unexplained'. However, more and more genetic causes underlying male infertility are emerging. RECENT FINDINGS: Research has begun to shed light on the causes of previously unexplained male infertility with clear links now established with infertility and meiotic defects in pairing, synapsis and recombination as well as increased levels of sperm aneuploidy. However, many have questioned whether this increase in sperm aneuploidy is observed in conceptuses or live birth; research suggests that this increase in aneuploidy is in fact paralleled in intracytoplasmic sperm injection (ICSI) conceptions. SUMMARY: Further research is warranted investigating the relationship between sperm aneuploidy and risk to ICSI conceptuses. Several infertility phenotypes have clearly been identified having a higher risk of sperm aneuploidy and may benefit from sperm aneuploidy screening prior to ICSI. Such screening would ultimately assist couples in deciding on the relative risk of undertaking ICSI and enable them to make informed decisions on whether to proceed with ICSI or to combine it with further screening such as preimplantation genetic diagnosis.

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)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-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 score0.983
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.156
GPT teacher head0.423
Teacher spread0.267 · 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

Citations32
Published2009
Admission routes1
Has abstractyes

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