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Record W2781026018 · doi:10.1016/j.ajog.2017.12.206

The past, present, and future of selective progesterone receptor modulators in the management of uterine fibroids

2017· review· en· W2781026018 on OpenAlexaff
Sukhbir S. Singh, Liane Belland, Nicholas Leyland, Sarah von Riedemann, Ally Murji

Bibliographic record

VenueAmerican Journal of Obstetrics and Gynecology · 2017
Typereview
Languageen
FieldMedicine
TopicUterine Myomas and Treatments
Canadian institutionsUniversity of TorontoMount Sinai HospitalMcMaster UniversityUniversity of CalgaryOttawa HospitalUniversity of Ottawa
FundersAllerganAbbVieBayer
KeywordsUterine fibroidsMedicineProgesterone receptorUlipristal acetateFertilityGynecologyObstetricsInternal medicineFamily planningPopulationEnvironmental health

Abstract

fetched live from OpenAlex

Uterine fibroids are common in women of reproductive age and can have a significant impact on quality of life and fertility. Although a number of international obstetrics/gynecology societies have issued evidence-based clinical practice guidelines for the management of symptomatic uterine fibroids, many of these guidelines do not yet reflect the most recent clinical evidence and approved indication for one of the key medical management options: the selective progesterone receptor modulator class. This article aims to share the clinical experience gained with selective progesterone receptor modulators in Europe and Canada by reviewing the historical development of selective progesterone receptor modulators, current best practices for selective progesterone receptor modulator use based on available data, and potential future uses for selective progesterone receptor modulators in uterine fibroids and other gynecologic conditions.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.028
GPT teacher head0.339
Teacher spread0.311 · 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 designNot applicable
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

Citations62
Published2017
Admission routes1
Has abstractno

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