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Record W2790033661 · doi:10.5489/cuaj.4907

A practical guide to female sexual dysfunction: An evidence-based review for physicians in Canada

2018· review· en· W2790033661 on OpenAlexaffvenueabout
Yonah Krakowsky, Ethan D. Grober

Bibliographic record

VenueCanadian Urological Association Journal · 2018
Typereview
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsSinai Health SystemWomen's College HospitalUniversity of Toronto
Fundersnot available
KeywordsErectile dysfunctionSexual dysfunctionSexual medicineFemale sexual dysfunctionSexual functionHuman sexualityMedicineReproductive healthMultidisciplinary approachClinical psychologyGynecologyIntensive care medicinePsychologyPsychiatryInternal medicinePopulationGender studiesPolitical science

Abstract

fetched live from OpenAlex

Introduction: Female sexual dysfunction (FSD) is characterized as distress related to sexual pain, sexual arousal, sexual desire, and/or orgasmic dysfunction.Despite prevalence rates similar to male sexual dysfunction, women with sexual complaints have been long under-evaluated, treated, and studied.Over the last decade there have been advances in the medical evaluation and management of FSD, however, there remains a paucity of clinical resources available for women in Canada with sexual dysfunction.Methods: The state of knowledge in the evaluation and treatment of FSD was reviewed.Recommendations are given for the practical evaluation and treatment of women with sexual symptoms that can be applied widely in Canada.Results: Approaches to the management and treatment of FSD are discussed with a focus on the practical application of diagnostic and therapeutic tools in the management of sexual pain, low desire, low arousal, and orgasmic dysfunction.Conclusions: There are evidence-based diagnostic and therapeutic approaches to FSD that can be broadly applied by Canadian physicians to improve access to female sexual medicine in Canada.

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)0.004
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.639
Threshold uncertainty score0.717

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.019
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0180.020
Science and technology studies0.0020.001
Scholarly communication0.0030.003
Open science0.0040.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0290.005

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 head0.159
GPT teacher head0.395
Teacher spread0.236 · 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 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

Citations49
Published2018
Admission routes3
Has abstractyes

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