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Record W2166944889 · doi:10.5489/cuaj.10026

The status of pelvic floor muscle training for women

2010· article· en· W2166944889 on OpenAlex
Andréa Marques, Lynn Stothers, Andrew Macnab

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Urological Association Journal · 2010
Typearticle
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsUniversity of British Columbia HospitalUniversity of British Columbia
FundersUniversiteit StellenboschCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsPelvic Floor MusclePelvic floorPhysical therapyPhysical medicine and rehabilitationMuscle strengthMedicineSurgery

Abstract

fetched live from OpenAlex

There is no consensus on the amount of exercise necessary to improve pelvic floor muscle (PFM) function. We reviewed the pathophysiology of PFM dysfunction and the evolution of PFM training regimens since Kegel introduced the concept of pelvic floor awareness and the benefits of strength. This paper also describes the similarities and differences between PFM and other muscular groups, reviews the physiology of muscle contraction and principles of muscle fitness and exercise benefits and presents the range of protocols designed to strengthen the PFM and improve function. We also discuss the potential application of new technology and methodologies. The design of PFM training logically requires multiple factors to be considered in each patient. Research that defines measures to objectively quantify the degree of dysfunction and the efficacy of training would be beneficial. The application of new technologies may help this process.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.241
Threshold uncertainty score0.445

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.250
Teacher spread0.233 · 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