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Record W2606493973 · doi:10.1016/j.jsxm.2017.03.086

PS-02-005 Radiofrequency with Cooling Device to Treat Vaginal Laxity: A Preliminary Report

2017· article· en· W2606493973 on OpenAlexaboutno aff
Michael Krychman

Bibliographic record

VenueThe Journal of Sexual Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRandomized controlled trialSexual functionPlaceboSurgeryVaginal dischargePhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

Vaginal laxity (VL) is an impactful medical condition that has been understudied. This study investigates the use of a patented cryogen-cooled monopolar radio frequency (CMRF) system that uses surface cooling and energy delivery to provide a non-ablative, minimally-invasive approach to create heat deep w/in vaginal tissue. The objective of this study was too determine the safety and effectiveness of a radio frequency with cooling device to treat the vaginal tissue in women following childbirth to improve VL. A prospective, longitudinal, randomized, blinded, placebo-controlled, multi-centre clinical study (first and only in the medical literature) was carried out for the treatment of VL. Subjects were randomized in a 2:1 ratio to either the active (90 J/cm2) or sham (≤1 J/cm2) treatment group. Nine sites were chosen in Italy, Spain, Canada and Japan. Subjects were followed up at 72 hrs, 10 days, and 1, 2, 3, and 6 months post-treatment. Patient reported outcomes included a 7-point Likert scale assessment for VL as well as a validated sexual function questionnaire.

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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.041
GPT teacher head0.338
Teacher spread0.296 · 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 designNon-randomized trial
Domainnot available
GenreEmpirical

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

Citations0
Published2017
Admission routes1
Has abstractyes

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