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Record W2037522182 · doi:10.1002/nau.20918

Continence products: Research priorities to improve the lives of people with urinary and/or fecal leakage

2010· review· en· W2037522182 on OpenAlexaff
Mandy Fader, Donna Z. Bliss, Alan Cottenden, Katherine Moore, Christine Norton

Bibliographic record

VenueNeurourology and Urodynamics · 2010
Typereview
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineFecal incontinenceUrinary incontinenceProduct (mathematics)Clinical trialIntensive care medicineSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Although many successful treatments for incontinence exist they are not effective or suitable for all people. Inconspicuous and dependable management with continence products and devices plays a crucial part in maintaining quality of life. We aim to briefly review what is known and not known in the field of continence products and devices and set out suggested priorities for research and development. The field of continence product research encompasses techniques and designs from basic laboratory science, through to clinical trials of products and to evaluations of service delivery models. Priorities for research include determining prevalence and costs of product use, development of patient reported outcomes, and development of methods for measuring skin health and for quantifying urine/faecal leakage. Product development priorities include better washable pads for women, absorbent products for fecal incontinence and flatus filters. Clinical trials of different product categories (e.g., devices for men) are needed, as are qualitative studies of patient experiences of product use.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0040.006
Science and technology studies0.0010.001
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0070.003

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 head0.033
GPT teacher head0.344
Teacher spread0.310 · 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

Citations39
Published2010
Admission routes1
Has abstractyes

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