MétaCan
Menu
Back to cohort
Record W2160745396

Assisted reproductive technologies to establish pregnancies in couples with an HIV-1-infected man.

2009· article· en· W2160745396 on OpenAlexaff
Elisabeth van Leeuwen, Sjoerd Repping, Jan M. Prins, Peter Reiss, Fulco van der Veen

Bibliographic record

VenuePubMed · 2009
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsMedicineAssisted reproductive technologySperm washingReproductive technologyArtificial inseminationHuman immunodeficiency virus (HIV)Intrauterine inseminationLife expectancyIn vitro fertilisationPregnancyGynecologySemenInfertilityObstetricsInseminationSpermImmunologyAndrologyPopulationEnvironmental healthBiology
DOInot available

Abstract

fetched live from OpenAlex

For HIV -1-infected men and women the introduction of highly active antiretroviral therapy (HART) in 1996 led to a spectacular increase in life expectancy and quality of life. In Western society where HART is readily available, HIV -1 is now considered to be a chronic disease and as a consequence quality of life is an important aspect for men and women with HIV-1. Many of them express the desire to father or mother a child. Assisted reproductive technologies, including intrauterine insemination (IUI), in vitro fertilisation (IVF) and intracytoplasmatic sperm injection (ICSI) in combination with semen washing have been used to decrease the risk of HIV -1 transmission in HIV-1-infected discordant couples with an HIV-1-infected man. This article aims to summarise the current state of the art of assisted reproductive technologies for couples with an HIV -1-infected man and to discuss current trends and dilemmas in the treatment of these couples.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.003

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 head0.029
GPT teacher head0.287
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 source (direct Gemma or distilled Codex), 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

Citations28
Published2009
Admission routes1
Has abstractyes

Explore more

Same venuePubMedSame topicHIV/AIDS Research and InterventionsFrench-language works237,207