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Record W2565705187 · doi:10.1055/s-0036-1597308

Medical Management of Endometriosis in Patients with Chronic Pelvic Pain

2016· review· en· W2565705187 on OpenAlexaff
Catherine Allaire, Paul J. Yong, Sukinah Alfaraj, Mohamed A. Bedaiwy

Bibliographic record

VenueSeminars in Reproductive Medicine · 2016
Typereview
Languageen
FieldMedicine
TopicEndometriosis Research and Treatment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEndometriosisPelvic painMedicineProgestinInfertilityAromataseEstrogenHormoneGynecologyInternal medicineBioinformaticsPregnancySurgeryBreast cancerCancerBiology

Abstract

fetched live from OpenAlex

Endometriosis is a common cause of pelvic pain in women of reproductive age. Traditional medical therapies are hormonal in nature, including estrogen-progestin contraceptives, progestins, and gonadotropin-releasing hormone (GnRH) agonists. Other hormonal options are androgens and aromatase inhibitors, with research also suggesting a possible role for GnRH antagonists and selective progesterone receptor modulators. Other than nonsteroidal anti-inflammatories, further work is required for nonhormonal therapies such as antiangiogenic and immune-modulating drugs. Medical treatment of endometriosis can be complex, and requires consideration of side effects, the anatomic type of endometriosis, role of surgery, current infertility or future fertility desires, and other contributors to pain (e.g., central sensitization). These factors should be discussed for each patient, to ensure personalized treatment and optimal outcomes.

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)0.000
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 score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.026
GPT teacher head0.352
Teacher spread0.327 · 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

Citations60
Published2016
Admission routes1
Has abstractyes

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