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Record W2905273766 · doi:10.1097/ogx.0000000000000628

Uterine Preservation vs Hysterectomy in Pelvic Organ Prolapse Surgery: A Systematic Review With Meta-analysis and Clinical Practice Guidelines

2018· review· en· W2905273766 on OpenAlexaff
Kate V. Meriwether, Danielle D. Antosh, Cedric K. Olivera, Shunaha Kim-Fine, Ethan M. Balk, Miles Murphy, Cara L. Grimes, Ambereen Sleemi, Ruchira Singh, Alexis A. Dieter, Catrina C. Crisp, David D. Rahn

Bibliographic record

VenueObstetrical & Gynecological Survey · 2018
Typereview
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineHysterectomyGynecologyClinical PracticeUterine prolapseGeneral surgerySurgeryObstetricsFamily medicine

Abstract

fetched live from OpenAlex

(Abstracted from Am J Obstet Gynecol 2018;219:129–146.e2) Hysterectomy performed at the time of pelvic organ prolapse (POP) repair allows the surgeon to gain access to tissues used for apical suspension. However, hysterectomy adds surgical time and costs and may increase morbidity.

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)0.007
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0100.019
Bibliometrics0.0040.005
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.306
GPT teacher head0.471
Teacher spread0.165 · 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 designMeta-analysis
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

Citations11
Published2018
Admission routes1
Has abstractyes

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