MétaCan
Menu
Back to cohort
Record W4406497570 · doi:10.1097/lgt.0000000000000869

A Narrative Review of the Vulvar Disease Literature With Images of Women of Color

2025· review· en· W4406497570 on OpenAlexaff
Gabriela Ashenafi, Ulrike Dehaeck, N A Madnani, Ebony Parker‐Featherstone, Natalie A. Saunders, Kathryn C. Welch, Arshpreet Kaur Mallhi, Hope K. Haefner

Bibliographic record

VenueJournal of Lower Genital Tract Disease · 2025
Typereview
Languageen
FieldMedicine
TopicFemale Genital Mutilation/Cutting Issues
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicinePopulationHealth careVulvar DiseasesDiseaseNarrativeScarcityVulvar cancerGerontologyFamily medicineDermatologyVulvaPathologyEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVE: To assess the existing literature on vulvar disease in women of color (WOC). METHODS: A narrative review was conducted to assess the literature on vulvar disease in WOC and evaluate the presence of images in this population. The search encompassed PubMed and OVID using relevant terms related to vulvar conditions and various groups of WOC. Case reports, as well as posters were excluded. Books on this topic were searched using these two search engines and Google, as well as the Taubman Health Sciences Library at the University of Michigan. This library contains numerous books on vulvar diseases commonly used by health care providers. RESULTS: This query identified 24 journal publications on vulvar diseases in WOC. Twenty-six books, commonly used by health care providers, were found to have been published with vulvar images of WOC. However, only 1 focused specifically on vulvar diseases in WOC. CONCLUSIONS: There is a notable scarcity of articles and books addressing vulvar conditions specifically in WOC. This gap in literature limits the understanding of how these conditions may uniquely affect this demographic population. Additional research and resources are essential to effectively represent and meet the health needs of WOC.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.065
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.013
GPT teacher head0.328
Teacher spread0.314 · 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 designSystematic review
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

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Lower Genital Tract DiseaseSame topicFemale Genital Mutilation/Cutting IssuesFrench-language works237,207