MétaCan
Menu
Back to cohort
Record W1917894405

Accelerated fatigue behavior and mechano-physical characterizations of in vitro physiological simulation of nitinol stents.

2012· article· en· W1917894405 on OpenAlexaff
K. Saïdane, Stéfania Polizu, L’H. Yahia

Bibliographic record

VenuePubMed · 2012
Typearticle
Languageen
FieldMedicine
TopicCoronary Interventions and Diagnostics
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsMaterials scienceBiomedical engineeringIn vitroComputer scienceEngineeringChemistry
DOInot available

Abstract

fetched live from OpenAlex

In this study, we have provided an experimental evaluation of the fatigue behavior of the nitinol (NiTi) endovascular device (peripheral stent). The accelerated fatigue tests were performed using arterial conditions, which mimicked actual physiological conditions. Natural, rubber latex-tubing materials were used to simulate human arteries. The equipment design and the test parameters used allowed for the simulation of a compliant artery and the application of circumferential forces to the device.The stent compliance values were good indicators for tracking the time evolution of fatigue behavior. Moreover, the analyses of changes on the surface morphology and on the chemical composition were used to establish a relationship between surface characteristics and peripheral stent response during 400 million cycles, which is equivalent to 10 yrs of human life. In order to determine the influence of the accelerated fatigue, an evaluation of both mechanical and surface characteristics was carried out before and after testing using the following tests and methods, respectively: radial hoop testing (RH), scanning electron microscope analysis (SEM), auger electron spectroscopy (AES), atomic absorption spectroscopy (AAS), and X-ray photoelectron spectroscopy (XPS). Under these experimental conditions, the studies have shown that after 400 million cycles, the tested stents did not demonstrate any mechanical failure. Moreover, the surface did not undergo any changes in its chemical composition. However, we did observe an increase in roughness and signs of pitting corrosion.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0010.000
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 head0.125
GPT teacher head0.333
Teacher spread0.208 · 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 designSimulation or modeling
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

Citations2
Published2012
Admission routes1
Has abstractyes

Explore more

Same venuePubMedSame topicCoronary Interventions and DiagnosticsFrench-language works237,207