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Functional Evaluation of an Artificial Anal Sphincter Using Shape Memory Alloys

2004· article· en· W2353466036 on OpenAlexaff
Yun Luo, Toshiyuki Takagi, Takeshi OKUYAMA, Shintaro Amae, Motoshi Wada, Kotaro Nishi, Takamichi Kamiyama, Tomoyuki Yambe, H. Matsuki

Bibliographic record

VenueASAIO Journal · 2004
Typearticle
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsInstitute of Aging
Fundersnot available
KeywordsSMA*Shape-memory alloyAnal sphincterSphincterFecal incontinenceAnimal modelMedicineOverheating (electricity)OcclusionBiomedical engineeringMaterials scienceSurgeryComputer scienceArtificial intelligenceEngineeringInternal medicine

Abstract

fetched live from OpenAlex

This article describes an implantable artificial anal sphincter using shape memory alloys and its in vivo assessment in porcine models. The new design was developed as a low invasive prosthesis with a simple structure to solve the problem of severe fecal incontinence in patients with hypoplastic sphincters or without anal sphincters and especially for ostomates. The artificial anal sphincter consists of two shape memory alloy (SMA) plates as the main functional parts to perform two basic functions when the SMA artificial sphincter is fitted around intestines (i.e., an occlusion at body temperature and an opening function on heating). Our previous assessments with short-term animal experiments revealed promising properties with the occlusion function of the device, although some complications, such as overpressure induced ischemia, heat burn, and infections, remained. This article addresses the concerns related to the practical use of the device, the power supplement to drive the actuator, and overheating protection of the device inside bodies. Results of chronic animal experiments of up to 4 weeks suggested great potential for the improved device.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.091
GPT teacher head0.340
Teacher spread0.249 · 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 designBench or experimental
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

Citations14
Published2004
Admission routes1
Has abstractyes

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