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Record W2093978807 · doi:10.4161/org.2.1.1757

The Possibility of Muscle Tissue Reconstruction Using Shape Memory Alloys

2005· article· en· W2093978807 on OpenAlex
Yun Luo, Masaru Higa, Shintaro Amae, Tomoyuki Yambe, Takeshi OKUYAMA, Toshiyuki Takagi, H. Matsuki

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.

Bibliographic record

VenueOrganogenesis · 2005
Typearticle
Languageen
FieldEngineering
Topic3D Shape Modeling and Analysis
Canadian institutionsHatch (Canada)
Fundersnot available
KeywordsAnatomyBiomedical engineeringComputer scienceMedicine

Abstract

fetched live from OpenAlex

Severe dysfunction of muscle tissues can be treated by transplantation but the success rate is still not high enough. One possibility instead is to replace the dysfunctional muscle with artificial muscles. This article introduces a unique approach using shape memory alloys (SMAs) to replace the anal sphincter muscle for solving the problem of fecal incontinence. The use of SMAs that exhibit a two-way shape memory effect allows the device to function like a sphincter muscle and facilitates simple design. In this article, we will give a brief introduction to the functional material-SMA-together with its medical applications, and will follow this with a description of the recent progress in research and development of an SMA-based artificial sphincter. The possibility of its commercialization will also be discussed.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.495
Threshold uncertainty score0.326

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.014
GPT teacher head0.225
Teacher spread0.211 · 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